diff --git a/.secrets.baseline b/.secrets.baseline
index 669be32..5b961d2 100644
--- a/.secrets.baseline
+++ b/.secrets.baseline
@@ -3,7 +3,7 @@
     "files": "^.secrets$|^.secrets.baseline$",
     "lines": null
   },
-  "generated_at": "2026-08-05T13:33:24Z",
+  "generated_at": "2026-08-06T17:18:31Z",
   "plugins_used": [
     {
       "name": "AWSKeyDetector"
@@ -82,7 +82,7 @@
         "hashed_secret": "52b44e0998fd3bcb1929ac25818191fae050cf1d",
         "is_secret": false,
         "is_verified": false,
-        "line_number": 662,
+        "line_number": 829,
         "type": "Secret Keyword",
         "verified_result": null
       }
diff --git a/add-biomed-multi-alignment-report.md b/add-biomed-multi-alignment-report.md
new file mode 100644
index 0000000..7d23cf1
--- /dev/null
+++ b/add-biomed-multi-alignment-report.md
@@ -0,0 +1,51 @@
+---
+name: New Nexus Package
+about: Submit a new Nexus package to Algorithm Nexus
+title: "feat(package): Add biomed-multi-alignment Nexus package"
+labels: "nexus-package"
+---
+
+## Description
+
+Adds the [biomed-multi-alignment](https://github.com/BiomedSciAI/biomed-multi-alignment)
+package as a new Nexus package. This package provides MAMMAL (Molecular Aligned
+Multi-Modal Architecture and Language), a 458M-parameter T5-style biomedical
+foundation model trained on over 2 billion biological samples across proteins,
+small molecules, and single-cell gene expression data.
+
+### Changes made
+
+- Created `packages/biomed-multi-alignment/nexus.yaml` with the Nexus package
+  definition.
+- Created `packages/biomed-multi-alignment/models/biomed.omics.bl.sm.ma-ted-458m/model.yaml`
+  with the HuggingFace model ID (`ibm-research/biomed.omics.bl.sm.ma-ted-458m`)
+  and vLLM plugin configuration (general plugin: `mammal`).
+- Added `biomed-multi-alignment` as a dependency to both the `ecosystem` and
+  `candidate` variants in `pyproject.toml`, pinned to release `0.2.5`
+  (`git+https://github.com/BiomedSciAI/biomed-multi-alignment@0.2.5`).
+  The package is **vllm-agnostic** (vLLM is an optional dependency via the
+  `[vllm]` extra), so it is added without extras for `ecosystem` and with
+  `[vllm]` for `candidate`.
+- Updated `uv.lock` and exported updated `requirements-ecosystem.txt` and
+  `requirements-candidate.txt`.
+
+### Variant classification
+
+The package declares `vllm` as an **optional** dependency (via the `[vllm]`
+extra in its `pyproject.toml`). It therefore belongs to both the **ecosystem**
+and **candidate** variants per the Variant Association Rules.
+
+## Additional Information
+
+The vLLM plugin (`vllm_mammal_plugin`) is located under the `mammal_vllm/`
+subdirectory of the repository and is included when installing with the `[vllm]`
+extra. The plugin is registered via the `vllm.general_plugins` entry point and
+exposes the MAMMAL model as a pooling-runner embedding model in vLLM.
+
+## I need help with this PR
+
+N/A — all steps completed successfully.
+
+## Related Issues
+
+N/A
diff --git a/packages/biomed-multi-alignment/models/biomed.omics.bl.sm.ma-ted-458m/model.yaml b/packages/biomed-multi-alignment/models/biomed.omics.bl.sm.ma-ted-458m/model.yaml
new file mode 100644
index 0000000..b120dd7
--- /dev/null
+++ b/packages/biomed-multi-alignment/models/biomed.omics.bl.sm.ma-ted-458m/model.yaml
@@ -0,0 +1,6 @@
+model:
+  id: ibm-research/biomed.omics.bl.sm.ma-ted-458m
+  vllm:
+    enabled: true
+    plugins:
+      general: mammal
diff --git a/packages/biomed-multi-alignment/nexus.yaml b/packages/biomed-multi-alignment/nexus.yaml
new file mode 100644
index 0000000..581972d
--- /dev/null
+++ b/packages/biomed-multi-alignment/nexus.yaml
@@ -0,0 +1,2 @@
+package:
+  name: biomed-multi-alignment
diff --git a/pyproject.toml b/pyproject.toml
index a6ef562..0d54b6f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,6 +18,7 @@ nexus = "algorithm_nexus.cli:main"
 
 [project.optional-dependencies]
 candidate = [
+  "biomed-multi-alignment[vllm]",
   "bmfm-targets[vllm]>=0.20.0",
   # CP 02/07/2026
   # Scanners are flagging opencv-python-headless==5.0.0.93 as
@@ -37,6 +38,7 @@ cli = [
   "typer>=0.25.0",
 ]
 ecosystem = [
+  "biomed-multi-alignment",
   "bmfm-targets",
   "gridfm-graphkit==0.8.1",
   "terrakit>=0.2.0",
@@ -88,6 +90,7 @@ conflicts = [
 [tool.uv.sources]
 bmfm-targets = { git = "https://github.com/BiomedSciAI/biomed-multi-omic.git" }
 tokamind = { git = "https://github.com/UKAEA-IBM-STFC-Fusion-FMs/tokamind", tag = "OS_v2.0" }
+biomed-multi-alignment = { git = "https://github.com/BiomedSciAI/biomed-multi-alignment", rev = "0.2.5" }
 
 [tool.uv-dynamic-versioning]
 enable = true
diff --git a/requirements-candidate.txt b/requirements-candidate.txt
index 2664f4a..2f81d18 100644
--- a/requirements-candidate.txt
+++ b/requirements-candidate.txt
@@ -1,7 +1,10 @@
 absl-py==2.5.0 \
     --hash=sha256:0c996f25c0490700fadabe6351630f6111534fa0ae252cc6d2014ea3b141135f \
     --hash=sha256:0f17b89f2a4eaaedc4f28c622998aa690564b3012a396a4ffad0821007fe03ba
-    # via tensorboard
+    # via
+    #   keras
+    #   tensorboard
+    #   tensorflow
 accelerate==1.14.0 \
     --hash=sha256:41b9c4377a54e0b460a959b0defa1b736e4ca0a2373252d9a539964c2afe3c8d \
     --hash=sha256:e94390c2863b873be18f623f9df48a0d8fe5eff13ea7f1a00092b0a7904888c6
@@ -146,6 +149,10 @@ apache-tvm-ffi==0.1.10 \
     #   tokenspeed-mla
     #   vllm
     #   xgrammar
+appnope==0.1.4 ; sys_platform == 'darwin' \
+    --hash=sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee \
+    --hash=sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c
+    # via ipykernel
 array-api-compat==1.15.0 \
     --hash=sha256:53c5f922491bf15f62847afafc4e39eedfae57d218988fefb8cce39c2a9b3dea \
     --hash=sha256:7b1b9c53269061403fd5f45a8de349f16e7887653328bfa0c5f2d45299ff0a8e
@@ -159,6 +166,14 @@ astor==0.8.1 \
     --hash=sha256:070a54e890cefb5b3739d19f30f5a5ec840ffc9c50ffa7d23cc9fc1a38ebbfc5 \
     --hash=sha256:6a6effda93f4e1ce9f618779b2dd1d9d84f1e32812c23a29b3fff6fd7f63fa5e
     # via depyf
+asttokens==3.0.2 \
+    --hash=sha256:3ecdbd8f2cc195f53ccada3a613538bb5f9ef6f6869129f13e03c30a677b8fe2 \
+    --hash=sha256:9da13157f5b28becde0bd374fc677dcd3c290614264eff096f167c469cd9f933
+    # via stack-data
+astunparse==1.6.3 \
+    --hash=sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872 \
+    --hash=sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8
+    # via tensorflow
 attrs==26.1.0 \
     --hash=sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309 \
     --hash=sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32
@@ -172,6 +187,65 @@ attrs==26.1.0 \
     #   somacore
     #   tiledb-cloud
     #   tiledbsoma
+autograd==1.9.1 \
+    --hash=sha256:7818c5c69ddf9efb7da74097bd741a4c7920133f41966f68537223a15ef798bc \
+    --hash=sha256:b788bae3fa010cbffb4cfb7b8ba2a3f0daa6072a8506da6164c779fe9cf3e05a
+    # via
+    #   autograd-gamma
+    #   lifelines
+autograd-gamma==0.5.0 \
+    --hash=sha256:f27abb7b8bb9cffc8badcbf59f3fe44a9db39e124ecacf1992b6d952934ac9c4
+    # via lifelines
+bcrypt==5.0.0 \
+    --hash=sha256:0c418ca99fd47e9c59a301744d63328f17798b5947b0f791e9af3c1c499c2d0a \
+    --hash=sha256:0c8e093ea2532601a6f686edbc2c6b2ec24131ff5c52f7610dd64fa4553b5464 \
+    --hash=sha256:137c5156524328a24b9fac1cb5db0ba618bc97d11970b39184c1d87dc4bf1746 \
+    --hash=sha256:200af71bc25f22006f4069060c88ed36f8aa4ff7f53e67ff04d2ab3f1e79a5b2 \
+    --hash=sha256:212139484ab3207b1f0c00633d3be92fef3c5f0af17cad155679d03ff2ee1e41 \
+    --hash=sha256:2b732e7d388fa22d48920baa267ba5d97cca38070b69c0e2d37087b381c681fd \
+    --hash=sha256:35a77ec55b541e5e583eb3436ffbbf53b0ffa1fa16ca6782279daf95d146dcd9 \
+    --hash=sha256:38cac74101777a6a7d3b3e3cfefa57089b5ada650dce2baf0cbdd9d65db22a9e \
+    --hash=sha256:3abeb543874b2c0524ff40c57a4e14e5d3a66ff33fb423529c88f180fd756538 \
+    --hash=sha256:3ca8a166b1140436e058298a34d88032ab62f15aae1c598580333dc21d27ef10 \
+    --hash=sha256:3cf67a804fc66fc217e6914a5635000259fbbbb12e78a99488e4d5ba445a71eb \
+    --hash=sha256:4bfd2a34de661f34d0bda43c3e4e79df586e4716ef401fe31ea39d69d581ef23 \
+    --hash=sha256:560ddb6ec730386e7b3b26b8b4c88197aaed924430e7b74666a586ac997249ef \
+    --hash=sha256:5b1589f4839a0899c146e8892efe320c0fa096568abd9b95593efac50a87cb75 \
+    --hash=sha256:5feebf85a9cefda32966d8171f5db7e3ba964b77fdfe31919622256f80f9cf42 \
+    --hash=sha256:611f0a17aa4a25a69362dcc299fda5c8a3d4f160e2abb3831041feb77393a14a \
+    --hash=sha256:61afc381250c3182d9078551e3ac3a41da14154fbff647ddf52a769f588c4172 \
+    --hash=sha256:64d7ce196203e468c457c37ec22390f1a61c85c6f0b8160fd752940ccfb3a683 \
+    --hash=sha256:64ee8434b0da054d830fa8e89e1c8bf30061d539044a39524ff7dec90481e5c2 \
+    --hash=sha256:741449132f64b3524e95cd30e5cd3343006ce146088f074f31ab26b94e6c75ba \
+    --hash=sha256:7aeef54b60ceddb6f30ee3db090351ecf0d40ec6e2abf41430997407a46d2254 \
+    --hash=sha256:801cad5ccb6b87d1b430f183269b94c24f248dddbbc5c1f78b6ed231743e001c \
+    --hash=sha256:83e787d7a84dbbfba6f250dd7a5efd689e935f03dd83b0f919d39349e1f23f83 \
+    --hash=sha256:89042e61b5e808b67daf24a434d89bab164d4de1746b37a8d173b6b14f3db9ff \
+    --hash=sha256:9d52ed507c2488eddd6a95bccee4e808d3234fa78dd370e24bac65a21212b861 \
+    --hash=sha256:9fffdb387abe6aa775af36ef16f55e318dcda4194ddbf82007a6f21da29de8f5 \
+    --hash=sha256:a71f70ee269671460b37a449f5ff26982a6f2ba493b3eabdd687b4bf35f875ac \
+    --hash=sha256:baade0a5657654c2984468efb7d6c110db87ea63ef5a4b54732e7e337253e44f \
+    --hash=sha256:c2388ca94ffee269b6038d48747f4ce8df0ffbea43f31abfa18ac72f0218effb \
+    --hash=sha256:c58b56cdfb03202b3bcc9fd8daee8e8e9b6d7e3163aa97c631dfcfcc24d36c86 \
+    --hash=sha256:cde08734f12c6a4e28dc6755cd11d3bdfea608d93d958fffbe95a7026ebe4980 \
+    --hash=sha256:d79e5c65dcc9af213594d6f7f1fa2c98ad3fc10431e7aa53c176b441943efbdd \
+    --hash=sha256:d8d65b564ec849643d9f7ea05c6d9f0cd7ca23bdd4ac0c2dbef1104ab504543d \
+    --hash=sha256:db99dca3b1fdc3db87d7c57eac0c82281242d1eabf19dcb8a6b10eb29a2e72d1 \
+    --hash=sha256:ddb4e1500f6efdd402218ffe34d040a1196c072e07929b9820f363a1fd1f4191 \
+    --hash=sha256:e3cf5b2560c7b5a142286f69bde914494b6d8f901aaa71e453078388a50881c4 \
+    --hash=sha256:ed2e1365e31fc73f1825fa830f1c8f8917ca1b3ca6185773b349c20fd606cec2 \
+    --hash=sha256:edfcdcedd0d0f05850c52ba3127b1fce70b9f89e0fe5ff16517df7e81fa3cbb8 \
+    --hash=sha256:f0ce778135f60799d89c9693b9b398819d15f1921ba15fe719acb3178215a7db \
+    --hash=sha256:f2347d3534e76bf50bca5500989d6c1d05ed64b440408057a37673282c654927 \
+    --hash=sha256:f3c08197f3039bec79cee59a606d62b96b16669cff3949f21e74796b6e3cd2be \
+    --hash=sha256:f632fd56fc4e61564f78b46a2269153122db34988e78b6be8b32d28507b7eaeb \
+    --hash=sha256:f6984a24db30548fd39a44360532898c33528b74aedf81c26cf29c51ee47057e \
+    --hash=sha256:f748f7c2d6fd375cc93d3fba7ef4a9e3a092421b8dbf34d8d4dc06be9492dfdd \
+    --hash=sha256:f8429e1c410b4073944f03bd778a9e066e7fad723564a52ff91841d278dfc822 \
+    --hash=sha256:fc746432b951e92b58317af8e0ca746efe93e66555f1b40888865ef5bf56446b
+    # via paramiko
+biomed-multi-alignment @ git+https://github.com/BiomedSciAI/biomed-multi-alignment@8cc56e9494b489ca86a63b76fa4cd2921f8af7f7
+    # via algorithm-nexus
 blake3==1.0.9 \
     --hash=sha256:0cdfeff65488089ef86f7587c76055ff72b28d28d10e427b547f5711477c376d \
     --hash=sha256:128a62136c9a39c7cb9fdaa5fb38471f2418853da7f5a89f31495735d0ba6f2c \
@@ -201,6 +275,20 @@ blake3==1.0.9 \
     --hash=sha256:dab59b324aa65c09e937d6c43de5de85ec9581627f4e79dcc9806d85b54a1c34 \
     --hash=sha256:eca281fedcbe5c56655bd5a4176e6036eddbbe57df96114a03838fce08b1e0ca
     # via vllm
+blosc2==4.10.1 \
+    --hash=sha256:77f2191c0be24c82d88cdcf7f45634602c996bd082ef9ff73a4d2a20b1340391 \
+    --hash=sha256:7b4b1dcc4da3198c4747bb88a62fc1664e3dc8fb727d505c85e283302ce7b8d4 \
+    --hash=sha256:7c66bd1f69683a63d4b9e5f8285ff951e1a0057bac5d2f68dee1564abaa8c277 \
+    --hash=sha256:acae1bc45fa0ba927270822b0f05d2f135309eebdcb1ea89383198996bc7702b \
+    --hash=sha256:b81e31335127eca1a6bfad235e45723c1b25fe0e8a99d5f830ea791d3da17839 \
+    --hash=sha256:b86f45f236ef2a812778ae2af7b530477db36693df4e464c29a75b6246b4dbaa \
+    --hash=sha256:c1196f12ccc19181743b7f66edceccf1981cf1b885c78a3a4f27b1a41e6541d4 \
+    --hash=sha256:d412cdf216e8fe4cffbe76a926c98c37a2419b14ba5c4be7f771f73e7d7b1840 \
+    --hash=sha256:d8dbaa028160992b03e3668578ef9668e09cdd11c2534646831a6a36d321cc8a \
+    --hash=sha256:e6649b94c28eb90a4c7dc5703cb67a5eb5121e891139c5ded2b75a172291d011 \
+    --hash=sha256:ee7f4b39a045fc77ec7d67381a95399d30885c208e71278c38f59b5ae29e8028 \
+    --hash=sha256:f37bb784c56b4fe11a0e23a011c609d08ebab0fe19fb2e75cea5e9ab13f9cbf2
+    # via tables
 bmfm-targets @ git+https://github.com/BiomedSciAI/biomed-multi-omic.git@8b5694a922be7ccb1d3ee5c280c4dcef2eb95df9
     # via algorithm-nexus
 boto3==1.43.56 \
@@ -220,6 +308,51 @@ branca==0.8.2 \
     --hash=sha256:2ebaef3983e3312733c1ae2b793b0a8ba3e1c4edeb7598e10328505280cf2f7c \
     --hash=sha256:e5040f4c286e973658c27de9225c1a5a7356dd0702a7c8d84c0f0dfbde388fe7
     # via folium
+cachebox==5.2.3 \
+    --hash=sha256:09c0340e9daa7b4530801e5a570cb0c1a1ad941a85d245d360020d3986d0e787 \
+    --hash=sha256:0a17aeb4e5b1c6ef1c3db8fc5186f9986e215ba5ea5a5d08baa45bcf55f261b2 \
+    --hash=sha256:10bedf96db8f9766cc956f9adcc623e604264e5d6fa2e255432f8c2ed7519143 \
+    --hash=sha256:26ae0b68979204d360327f4c0725cfdc95cfc34ab73ab1a8f528e3bd2f6d023c \
+    --hash=sha256:2a1e7d3cb8a5e7e68996a8619e3ef8771a124d14568c251f9e586eba88d759c1 \
+    --hash=sha256:2f1e086ab5ffd082a68bb63699d517655a59b06414927bfc84e01df91b81e34d \
+    --hash=sha256:405f9cc8492fc9d953b5a6b9e2b661e99583755c6639ab8d09a287fdf336503c \
+    --hash=sha256:40ac878af00d5969862c1f6bc076de1e34ca248662fce6aecca1761f52e33e32 \
+    --hash=sha256:410b67baa99d433644199b11289627f7ebba4ee5786f95ca9858f238afcee157 \
+    --hash=sha256:41e99c1240106d39b63ce7868a6cd8c9da9243fef08848b85d428164e0769fd2 \
+    --hash=sha256:432ca62b99f7eafc21af669d76c88c1b7377db179b89fb6fca3ea93b8f9fff19 \
+    --hash=sha256:55003089d21c2f5515089c307be063b45558e884a4a1cc9593944374c89975c4 \
+    --hash=sha256:5e48a405f699fb001b8af120a6e0b4a981277f84eb5dd66a1faa21e4b6fe9485 \
+    --hash=sha256:5fee33549877c03c2494ec5359a57a7667f872fe8e296a7f39d3dfe08dd3914c \
+    --hash=sha256:64057caa6b741320655cd3c5997fe642dae5dbff571eb530e6f53e58272bb43b \
+    --hash=sha256:649d18399f13735bb82daa33800196f815529c49e967767c40ca221723e68afa \
+    --hash=sha256:67548a05cd41fcc4f7af80a2f97f742fef3d436537ac2e1a1dce0fcba5d41190 \
+    --hash=sha256:6a94d0da8133b3a0707ae11c9ea321f8fc37e3b5a14517019a05d632218b0f56 \
+    --hash=sha256:82e7002dd343afeeba2fcf0e483131b342a27ec3bc34b2214dc617691bda40d6 \
+    --hash=sha256:8342ff350ce86f062492752d612e9f056ac5dc56375713d75c3bf6e83b4d18db \
+    --hash=sha256:85ccd827193b3e3e887a88a16b88ef7ed174e7e65be515b5253322aa75e665c3 \
+    --hash=sha256:8cbfc007ea78af61d75d7d26e5854df53dc5da6877d074afd4b4696c074f4ee7 \
+    --hash=sha256:94aae393ec1d9b26565d346445bb6afa3963d2a0d3eb5e4188d0e510fab871a0 \
+    --hash=sha256:9527c5c70f8735f2d696331d8bcf77254f03b4dc8542046807823bd36ed4e8ba \
+    --hash=sha256:a189a780c3ccd7b9d157074ba6bf3e191e522b39abbdb590075111851f02d50d \
+    --hash=sha256:a4b7559fa4994c4032dd07466c2041d57e055feb814762e1f73f4e8beef188d0 \
+    --hash=sha256:a8b0b575066fc09f6fae0d4bd30d6ff56584a6870cbe7d202916c5e0d725cfd4 \
+    --hash=sha256:adcedfcfcb933b21e7fdcfe560c79887bc8287abceab0586aa3730417dd0277d \
+    --hash=sha256:b1f68246685aa739bbbd2734befb1465363a1e1042407c154feadb065f17a099 \
+    --hash=sha256:b5ff26bfd8f7e95b3becf6d5f65c25edaca50fa68078868648b70d79bcccc260 \
+    --hash=sha256:c48c10e498d573511aafbd545570e7f43b40a7428dc282183bf5adc334d9e1a8 \
+    --hash=sha256:c7f0c72c51a3a9e7049ea6ff2a43cd3877ab7fee966eb65771a59621563b75e3 \
+    --hash=sha256:ccbdc54a6c4b5758408c1083bdfa217bd382894a8331c7d0a54b84ba0cf51e5b \
+    --hash=sha256:cfd69114141ab362acaa2099e425a1b965cf7b021a539a4e953143d593930b74 \
+    --hash=sha256:dcc5edb6ecf2b516e90b773d232360c5e4ed8fdcda038b19441da2ed9cf208ab \
+    --hash=sha256:df5135a168f143d186b1cc3be0ca16b66446897ab5cedc03bd80bcc926fcd403 \
+    --hash=sha256:e51d9c59006b53447f806145406eb37a7fc3c25553d4fd24c3887f3b268d214e \
+    --hash=sha256:f22732d0d69bb84ad2dca7480bffdfd0430c647152d488936e152ecbbfee52fb \
+    --hash=sha256:f3162758792626685ec34950eedd565d015b115d0ff0d751d2716031fc32d51b \
+    --hash=sha256:f3d628b816e28a6e7661d460e02dd5b421247cc2cd275814f80ea79621245fc4 \
+    --hash=sha256:f57afada3d9327adf87f3b5cf0094348c6fd49354ab2e9bd20b044648eb094ae \
+    --hash=sha256:f81474dc19d3865fa5e57263f834bc6bbc00e471a594fb9d934ed552732c02fd \
+    --hash=sha256:fa325306084aa2dc0b21e07723d7700f4d43dece3732c7fdaf7a269dc5e35aa7
+    # via deepdiff
 cachetools==7.1.7 \
     --hash=sha256:a3e2a00b14d8f8a6b70c1dae7b4685e7ad3bc965c5b42124a2d6ce895da6cf50 \
     --hash=sha256:ef98ef375ad188819ef2f9b3645e3987f4b8c5b7550e436ad998c2de78296df0
@@ -270,7 +403,7 @@ certifi==2026.7.22 \
     #   scanpy
     #   sentry-sdk
     #   tiledb-cloud
-cffi==2.1.1 ; implementation_name == 'pypy' \
+cffi==2.1.1 ; implementation_name == 'pypy' or platform_python_implementation != 'PyPy' \
     --hash=sha256:046bfc24911b37851ee1b51aab8bffe713d89c68c6a057b09484ce9fd5f69b4e \
     --hash=sha256:19ee6127ee34de7d83ce3d371ebc5ed91addbdcc39f9ab15ce4eb35a4e534971 \
     --hash=sha256:1aa5645c30469b09530c4ebca77ebf8f17618293c58f8549cb1a543a50236e7d \
@@ -300,6 +433,7 @@ cffi==2.1.1 ; implementation_name == 'pypy' \
     --hash=sha256:fcd22650c908d7b7da162bbfaab594a1227a15d1643a98c68b122ac642fa2264
     # via
     #   cryptography
+    #   pynacl
     #   pyzmq
 cftime==1.6.5 \
     --hash=sha256:18ab754805233cdd889614b2b3b86a642f6d51a57a1ec327c48053f3414f87d8 \
@@ -348,9 +482,16 @@ charset-normalizer==3.4.9 \
     --hash=sha256:e4fd89cc178bced6ad29cb3e6dd4aa63fa5017c3524dbd0b25998fb64a87cc8b \
     --hash=sha256:fe2c7201c642b7c308f1675355ad7ff7b66acfe3541625efe5a3ad38f29d6115
     # via requests
+choix==0.4.1 \
+    --hash=sha256:15fe145ffc194dc6b4ba5a44ef24667fa0107578fb5b36723ab0b5e87eeae29f \
+    --hash=sha256:7c85d13845400932508c45a6a6a3e7a44f637969ffd506e1c7f5db07de1560b4
+    # via fuse-med-ml
 clearml==1.18.0 \
     --hash=sha256:fe53ffcfdb0799150ad5ae1ca95bdbd568e570cbde2e35a65474e36606a899d0
-    # via bmfm-targets
+    # via
+    #   biomed-multi-alignment
+    #   bmfm-targets
+    #   fuse-med-ml
 click==8.4.2 \
     --hash=sha256:9a6cea6e60b17ebe0a44c5cc636d94f09bd66142c1cd7d8b4cd731c4917a15f6 \
     --hash=sha256:e6f9f66136c816745b9d65817da91d61d957fb16e02e4dcd0552553c5a197b76
@@ -358,6 +499,7 @@ click==8.4.2 \
     #   cligj
     #   dask
     #   flashinfer-python
+    #   fuse-med-ml
     #   huggingface-hub
     #   mercantile
     #   rasterio
@@ -382,9 +524,15 @@ colorama==0.4.6 ; sys_platform == 'win32' \
     --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
     # via
     #   click
+    #   ipython
     #   loguru
+    #   pytest
     #   tqdm
     #   typer
+comm==0.2.3 \
+    --hash=sha256:2dc8048c10962d55d7ad693be1e7045d891b7ce8d999c97963a5e3e99c055971 \
+    --hash=sha256:c615d91d75f7f04f095b30d1c1711babd43bdc6419c1be9886a85f2f4e489417
+    # via ipykernel
 compressed-tensors==0.17.0 \
     --hash=sha256:15c20d06bdbcf35b51fc99fd125e7b9be1e1855567c33b7a46dfac26ad6fb126 \
     --hash=sha256:4a1b89b508f7efb8ffb4eee8a6e69e0452d9b080cae130146025c64fbe9fa9aa
@@ -429,6 +577,37 @@ contourpy==1.3.3 \
     --hash=sha256:e4e6b05a45525357e382909a4c1600444e2a45b4795163d3b22669285591c1ae \
     --hash=sha256:fd914713266421b7536de2bfa8181aa8c699432b6763a0ea64195ebe28bff6a9
     # via matplotlib
+cryptography==50.0.0 \
+    --hash=sha256:031e2d5dd4bb9caa3ca9c82e5a197fd8ae680232cee62603d1a813f3f07e3d03 \
+    --hash=sha256:06a32a980526a6ab9a4b9bf8f7385800791e2bb960903cb6b530e4817509a3b7 \
+    --hash=sha256:07949c449a1abcf60d1ee6e88956d89404c7df3c8258f46589e912988e551987 \
+    --hash=sha256:105110f43a471dbd0060b9c9516cb8a6a79233631a04cc2ba16f28323ac6e025 \
+    --hash=sha256:1489e263a8048bb8b6a8bac662eb2d402ea5d2b7b4699b72f385f1e2772db105 \
+    --hash=sha256:2a8183b489dc1f7f80f135780fadc1108f14b31b8a40411c7a5b17425f65f28b \
+    --hash=sha256:37fdb0d0111f1e2ff07139dfb79f1b49531f8e213c46f1163dd7642979b58c47 \
+    --hash=sha256:65c2c3add92b45fd0709db8594536aea39c2a67af0e27ffcf049c498501140b7 \
+    --hash=sha256:6e7d61120573a7f2cd94cc095f9e81f6967c61ccdf194285aa143ecec8e0b708 \
+    --hash=sha256:7cec5b856506da6defb290f30c9ee687d5f5e8cb0bd3f6459dde43b0b4fa40ef \
+    --hash=sha256:82148ec5bddac30b51a5b3c1945075f896fa022cb93f8e4a01e9f6ee95292c5f \
+    --hash=sha256:828743d939e9629bc267b8e2d08d8bb67cd4319c771a33d4b18b22dd8fb7440a \
+    --hash=sha256:8d89f3976b10b4ce31118de72329025f70d2c6ead14a8217c5514dd2c6d5a78f \
+    --hash=sha256:900131fafd8aead39ac7dd3a7e833be754c17a95cfd91221636949fe4eb0aa8a \
+    --hash=sha256:910e1d2668e7de9648f2bcee30e180db2a6b15c30f887d7c4c93ddf96e3992e3 \
+    --hash=sha256:a1b30560f2acc95aa8b2e06e716a13dbfc97314747b80d9707e307f77b40d6b3 \
+    --hash=sha256:a91296cb61e8df6f86d0c19cc4068228da256bf59bf86049fbd821084565327f \
+    --hash=sha256:b42a28c1844fd9de8f3f7d540e36b66f3a9c83fceac7170ebc7a6a19edd9dcae \
+    --hash=sha256:bd1c592e4d5974f0d08d4888e432157adba757c66da0246918e43677fafa2d30 \
+    --hash=sha256:c87f62a3d3b9888ed0fdde100ec06aa61ca9cd44bad9057d1dff9a516b5f5bb9 \
+    --hash=sha256:ccdc4a71a4dabae05de219404f9f4abc38e3b58422177ff93d0da05967dafa07 \
+    --hash=sha256:d24fead1d4d076e1bfb006dcec392074a3cd8d7b4fc8a595aa64073b2b7a96ba \
+    --hash=sha256:d764dcf130c428ef66786f866dd750f53182bc608813489915e9fc106bb0c82f \
+    --hash=sha256:e722f16708d854fe924790e051061f6704a472c3bac347b6fd88033ea8dd0dc5 \
+    --hash=sha256:eeac2acb5a20ed25e0ad6d1df9891a520b78b404266b6d11778f25d5d691a6c9 \
+    --hash=sha256:f89831ef99dd7dd169ab06d63a831adb9e20a87aac6d380266bbda5823349169 \
+    --hash=sha256:fd9192b7b70c573d7f214eb1ae35e00d359f6f5e4b27c7e21e30de1fc6204645
+    # via
+    #   paramiko
+    #   pyjwt
 cuda-bindings==13.3.1 \
     --hash=sha256:18c8c167c8907b8f02531ca810534315c458dabef31f7965095619bf647b9202 \
     --hash=sha256:2732904099e0a4d4db774a5fc6d91ee95fae065b4d2ecabb4968c5fe2406c9d7 \
@@ -486,6 +665,22 @@ dataclasses-json==0.6.7 \
     --hash=sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a \
     --hash=sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0
     # via sentinelhub
+debugpy==1.8.21 \
+    --hash=sha256:13678151fc401e2d68c9880b91e28714f797d40422994572b24560ef80910a88 \
+    --hash=sha256:2c2ae706dec41d99a9ca1f7ebc987a83e65578363be6f6b3ac9067504917fae1 \
+    --hash=sha256:4743373c1cac7f9e74a1b9915bf1dbe0e900eca657ffb170ae07ac8363205ae9 \
+    --hash=sha256:9f96713896f39c3dff0ee841f47320c3f2983d33c341e009361bb0ebc79adc4e \
+    --hash=sha256:a3c53278e84c94e11bd87c53970ec391d1a67396c8b22609fcac576520e611a6 \
+    --hash=sha256:aa648733047443eb1d07682c4ef287d36a54507b643ffdf38b09a3ef002c72a0 \
+    --hash=sha256:b1e37d333663c8851516a47364ef473da127f9caebe4417e6df6f5825a7e9a92 \
+    --hash=sha256:bd7ba9dd3daa7c2f942c6ca8d4695a16bf9ac16b63615261c7982bc74f7ed20c \
+    --hash=sha256:c193d474f0a211191f2b4449d2d06157c689013035bd952f3b617e0ef422b176 \
+    --hash=sha256:ecbd158386c31ffe71d46f72d44d56e66331ab9b16cad649156d514368f23ab2
+    # via ipykernel
+deepdiff==9.1.0 \
+    --hash=sha256:07e9e366fab4297755153c4eab795ad4ef3cbd0d51660e847f5751c6bd727687 \
+    --hash=sha256:80c0460e1993b04f6f0ca79abf25548b129fd218478c4ebb08f80560f5d10610
+    # via fuse-med-ml
 deprecated==1.3.1 \
     --hash=sha256:597bfef186b6f60181535a29fbe44865ce137a5079f295b479886c82729d5f3f \
     --hash=sha256:b1b50e0ff0c1fddaa5708a2c6b0a6588bb09b892825ab2b214ac9ea9d92a5223
@@ -551,14 +746,25 @@ einops==0.8.2 \
     #   flashinfer-python
     #   quack-kernels
     #   terratorch
+    #   torch-einops-utils
     #   torchgeo
+    #   vit-pytorch
     #   vllm
+    #   x-transformers
+einx==0.4.3 \
+    --hash=sha256:47ce54a0144f6dffcfacdd8fe2cc9e2e5e6485dda2471330ab75ee747dd22f39 \
+    --hash=sha256:be7d81ea1908b9f00e4a467840998fc483c33aa32aaaaa3ada6c8386f693edf9
+    # via x-transformers
 email-validator==2.3.0 \
     --hash=sha256:80f13f623413e6b197ae73bb10bf4eb0908faf509ad8362c5edeb0be7fd450b4 \
     --hash=sha256:9fc05c37f2f6cf439ff414f8fc46d917929974a82244c20eb10231ba60c54426
     # via
     #   fastapi
     #   pydantic
+executing==2.2.1 \
+    --hash=sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4 \
+    --hash=sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017
+    # via stack-data
 fast-array-utils==1.5 \
     --hash=sha256:08a349dc9cbcfaa59b98bf00e7aa36ef11ddef91128784a65d2eb63c4681b282 \
     --hash=sha256:6151ecbb649d74f38927f1a3b67918ca3d65b1f9d2528cfaf9abb4d1ae5762e1
@@ -640,6 +846,9 @@ flashinfer-python==0.6.14 \
     --hash=sha256:d124369346a3d48eac67e31c42f7a3c813bcc0abc10e2e36db413b7b3dfd97df \
     --hash=sha256:f4da8b5e005601784e85e0dcaa3389f908ee2d32c2560142d67124ab10e4a070
     # via vllm
+flatbuffers==25.12.19 \
+    --hash=sha256:7634f50c427838bb021c2d66a3d1168e9d199b0607e6329399f04846d42e20b4
+    # via tensorflow
 focal-loss-torch @ git+https://github.com/mathiaszinnen/focal_loss_torch.git@69fd65795f2688c2c302029f383f1b58978c1123
     # via bmfm-targets
 folium==0.20.0 \
@@ -666,6 +875,14 @@ fonttools==4.63.0 \
     --hash=sha256:ee08ebfa58f6e1aeff5697ab9582105bb620008c1caafb681e4c557e7483027b \
     --hash=sha256:ef3048ef05dbb552b89817713d9cac912e00d0fde4a3105c00d29e52e10c89af
     # via matplotlib
+formulaic==1.2.2 \
+    --hash=sha256:0f84ff49e3fc9dc0e68ab08a0a9427874021aa6c558e66b44dc634a35739b09b \
+    --hash=sha256:c99e8f11ff7d327eaecaf63855ca69b7fa0da100ad6c0041ef80912fbac667e6
+    # via lifelines
+frozendict==2.4.7 \
+    --hash=sha256:972af65924ea25cf5b4d9326d549e69a9a4918d8a76a9d3a7cd174d98b237550 \
+    --hash=sha256:e478fb2a1391a56c8a6e10cc97c4a9002b410ecd1ac28c18d780661762e271bd
+    # via einx
 frozenlist==1.8.0 \
     --hash=sha256:032efa2674356903cd0261c4317a561a6850f3ac864a63fc1583147fb05a79b0 \
     --hash=sha256:03ae967b4e297f58f8c774c7eabcce57fe3c2434817d4385c50661845a058121 \
@@ -734,6 +951,14 @@ furl==2.1.4 \
     --hash=sha256:877657501266c929269739fb5f5980534a41abd6bbabcb367c136d1d3b2a6015 \
     --hash=sha256:da34d0b34e53ffe2d2e6851a7085a05d96922b5b578620a37377ff1dbeeb11c8
     # via clearml
+fuse-med-ml==0.4.1 \
+    --hash=sha256:df7b8a67b34f96917e3d40308fa6d6a36f028d7b1c48934263524a1149f8fafd \
+    --hash=sha256:f7d1a0931868cd319627bfd201c8c0312f08901331c68f02afee1fbf5cd77398
+    # via biomed-multi-alignment
+gast==0.7.0 \
+    --hash=sha256:0bb14cd1b806722e91ddbab6fb86bba148c22b40e7ff11e248974e04c8adfdae \
+    --hash=sha256:99cbf1365633a74099f69c59bd650476b96baa5ef196fec88032b00b31ba36f7
+    # via tensorflow
 geographiclib==2.1 \
     --hash=sha256:6a6545e6262d0ed3522e13c515713718797e37ed8c672c31ad7b249f372ef108 \
     --hash=sha256:e2a873b9b9e7fc38721ad73d5f4e6c9ed140d428a339970f505c07056997d40b
@@ -753,6 +978,10 @@ geopy==2.5.0 \
     --hash=sha256:7b6c849f18108dcce4faa3d614e2801107b465f7b05fd3c1db9db12e225ae950 \
     --hash=sha256:8ad8cc226b505ca4d272ae9a2eeba08b8a2c565fc9a04eaefc33ad49c32b51aa
     # via contextily
+google-pasta==0.2.0 \
+    --hash=sha256:b32482794a366b5366a32c92a9a9201b107821889935a02b3e51f6b432ea84ed \
+    --hash=sha256:c9f2c8dfc8f96d0d5808299920721be30c9eec37f2389f28904f454565c8a16e
+    # via tensorflow
 googleapis-common-protos==1.75.0 \
     --hash=sha256:53a062ff3c32552fbd62c11fe23768b78e4ddf0494d5e5fd97d3f4689c75fbbd \
     --hash=sha256:961ed60399c457ceb0ee8f285a84c870aabc9c6a832b9d37bb281b5bebde43ed
@@ -784,6 +1013,7 @@ grpcio==1.83.0 \
     # via
     #   opentelemetry-exporter-otlp-proto-grpc
     #   tensorboard
+    #   tensorflow
 h11==0.16.0 \
     --hash=sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1 \
     --hash=sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86
@@ -791,28 +1021,39 @@ h11==0.16.0 \
     #   httpcore
     #   httpcore2
     #   uvicorn
-h5py==3.16.0 \
-    --hash=sha256:099f2525c9dcf28de366970a5fb34879aab20491589fa89ce2863a84218bb524 \
-    --hash=sha256:171038f23bccddfc23f344cadabdfc9917ff554db6a0d417180d2747fe4c75a7 \
-    --hash=sha256:18f2bbcd545e6991412253b98727374c356d67caa920e68dc79eab36bf5fedad \
-    --hash=sha256:2b2c02b0a160faed5fb33f1ba8a264a37ee240b22e049ecc827345d0d9043074 \
-    --hash=sha256:370a845f432c2c9619db8eed334d1e610c6015796122b0e57aa46312c22617d9 \
-    --hash=sha256:39c2838fb1e8d97bcf1755e60ad1f3dd76a7b2a475928dc321672752678b96db \
-    --hash=sha256:42108e93326c50c2810025aade9eac9d6827524cdccc7d4b75a546e5ab308edb \
-    --hash=sha256:42b012933a83e1a558c673176676a10ce2fd3759976a0fedee1e672d1e04fc9d \
-    --hash=sha256:656f00e4d903199a1d58df06b711cf3ca632b874b4207b7dbec86185b5c8c7d4 \
-    --hash=sha256:698dd69291272642ffda44a0ecd6cd3bda5faf9621452d255f57ce91487b9794 \
-    --hash=sha256:7e420b539fb6023a259a1b14d4c9f6df8cf50d7268f48e161169987a57b737ff \
-    --hash=sha256:9300ad32dea9dfc5171f94d5f6948e159ed93e4701280b0f508773b3f582f402 \
-    --hash=sha256:96b422019a1c8975c2d5dadcf61d4ba6f01c31f92bbde6e4649607885fe502d6 \
-    --hash=sha256:a0dbaad796840ccaa67a4c144a0d0c8080073c34c76d5a6941d6818678ef2738 \
-    --hash=sha256:c5313566f4643121a78503a473f0fb1e6dcc541d5115c44f05e037609c565c4d \
-    --hash=sha256:dfc21898ff025f1e8e67e194965a95a8d4754f452f83454538f98f8a3fcb207e \
-    --hash=sha256:ff24039e2573297787c3063df64b60aab0591980ac898329a08b0320e0cf2527
+h2==4.4.1 \
+    --hash=sha256:0e25f1462b23c9cb82d9eb02e28bc706dac2a68cb457c6a0d74d63c8a2a5d0e6 \
+    --hash=sha256:4e866ffb1a869ae14dd9b5e6beb5c24a13da0495ad72b65925ded182521c1516
+    # via httpx
+h5py==3.14.0 \
+    --hash=sha256:0cbd41f4e3761f150aa5b662df991868ca533872c95467216f2bec5fcad84882 \
+    --hash=sha256:2372116b2e0d5d3e5e705b7f663f7c8d96fa79a4052d250484ef91d24d6a08f4 \
+    --hash=sha256:554ef0ced3571366d4d383427c00c966c360e178b5fb5ee5bb31a435c424db0c \
+    --hash=sha256:6da62509b7e1d71a7d110478aa25d245dd32c8d9a1daee9d2a42dba8717b047a \
+    --hash=sha256:aa4b7bbce683379b7bf80aaba68e17e23396100336a8d500206520052be2f812 \
+    --hash=sha256:ae18e3de237a7a830adb76aaa68ad438d85fe6e19e0d99944a3ce46b772c69b3 \
+    --hash=sha256:bf4897d67e613ecf5bdfbdab39a1158a64df105827da70ea1d90243d796d367f \
+    --hash=sha256:d90e6445ab7c146d7f7981b11895d70bc1dd91278a4f9f9028bc0c95e4a53f13 \
+    --hash=sha256:e0045115d83272090b0717c555a31398c2c089b87d212ceba800d3dc5d952e23 \
+    --hash=sha256:e8cbaf6910fa3983c46172666b0b8da7b7bd90d764399ca983236f2400436eeb \
+    --hash=sha256:ef9603a501a04fcd0ba28dd8f0995303d26a77a980a1f9474b3417543d4c6174
     # via
     #   anndata
+    #   fuse-med-ml
+    #   hdf5plugin
+    #   keras
     #   scanpy
+    #   tensorflow
     #   terratorch
+hdf5plugin==7.0.0 \
+    --hash=sha256:0f3ba9f4e2a370340b45e7042d1b1b1577ab259c1ddf00956264836fa33052ef \
+    --hash=sha256:1a4cb2207ec3ac538fc728e4596e9e49aed6c4487a641071fb370c04a361e7bf \
+    --hash=sha256:2e052af8d7848e8bac92646584617503a08bb9b466cfa810a49ecd93e89b7ffa \
+    --hash=sha256:4ad4ab0d3367699d132e61b1cc382a0c640a7dba56536e5105508205ebbe8762 \
+    --hash=sha256:97ea4ff6114223c5e8ccce7e23cc6cd398b58c02f4e988e967aeea914fcb8030 \
+    --hash=sha256:e0ff0a81e6319575ffc8bf230b8df43f3f19f6fe96843e113e04c5ba9f7f3141 \
+    --hash=sha256:e6e6b1f8b0c4d2ca87e616ddc31d08330b36207e466357040f95269e5e0401c8
+    # via fuse-med-ml
 hf-xet==1.6.0 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64' \
     --hash=sha256:0e6e21fa3cdfcdcd76748564bf593870a5e013f47d97cf10aed63aa222cff5b7 \
     --hash=sha256:2e58454a340b3556dfa4972d5451aff4fba8dd42a236600ba1a1d2b1514f0fef \
@@ -827,6 +1068,10 @@ hf-xet==1.6.0 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or
 hic-straw==1.3.1 \
     --hash=sha256:fb0f878127f6b1d096303c67793477c83fddf3f4a1a8e29a9d92952634989876
     # via bmfm-targets
+hpack==4.2.0 \
+    --hash=sha256:0895cfa3b5531fc65fe439c05eb65144f123bf7a394fcaa56aa423548d8e45c0 \
+    --hash=sha256:858ac0b02280fa582b5080d68db0899c62a80375e0e5413a74970c5e518b6986
+    # via h2
 httpcore==1.0.9 \
     --hash=sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55 \
     --hash=sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8
@@ -853,6 +1098,7 @@ httpx==0.28.1 \
     --hash=sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad
     # via
     #   anthropic
+    #   blosc2
     #   diffusers
     #   fastapi
     #   fastapi-cloud-cli
@@ -871,6 +1117,7 @@ huggingface-hub==1.26.0 \
     #   accelerate
     #   bmfm-targets
     #   diffusers
+    #   fuse-med-ml
     #   peft
     #   segmentation-models-pytorch
     #   terrakit
@@ -886,8 +1133,14 @@ hydra-core==1.3.4 \
     --hash=sha256:ad0f7b05a0242255a8984d5a4ed2f6847f7b783ed727368a2c0155ec52d6c34c \
     --hash=sha256:e58683692904a09f1fdfffa1a9b86bfd94e215b59f1ee17e7cd7d92738090d33
     # via
+    #   biomed-multi-alignment
     #   bmfm-targets
+    #   fuse-med-ml
     #   lightly
+hyperframe==6.1.0 \
+    --hash=sha256:b03380493a519fce58ea5af42e4a42317bf9bd425596f7a0835ffce80f1a42e5 \
+    --hash=sha256:f630908a00854a7adeabd6382b43923a4c4cd4b821fcb527e6ab9e15382a3b08
+    # via h2
 idna==3.18 \
     --hash=sha256:7f952cbe720b688055e3f87de14f5c3e5fdaa8bc3928985c4077ca689de849a2 \
     --hash=sha256:ffb385a7e039654cef1ab9ef32c6fafe283c0c0467bba1d9029738ce4a14a848
@@ -940,10 +1193,40 @@ importlib-metadata==9.0.0 \
     # via
     #   diffusers
     #   tiledb-cloud
+iniconfig==2.3.0 \
+    --hash=sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730 \
+    --hash=sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12
+    # via pytest
 interegular==0.3.3 \
     --hash=sha256:b0c07007d48c89d6d19f7204972d369b2a77222722e126b6aa63aa721dc3b19c \
     --hash=sha256:d9b697b21b34884711399ba0f0376914b81899ce670032486d0d048344a76600
     # via lm-format-enforcer
+interface-meta==2.0.1 \
+    --hash=sha256:902bd9a95a12f195f15753a1080075d4eca7a2cb934fac7ac03c9e362b50796a \
+    --hash=sha256:f38016bef9a4429b6d0792d809be7b65e9781820c674bf7f463999086b6e6323
+    # via formulaic
+invoke==3.0.3 \
+    --hash=sha256:437b6a622223824380bfb4e64f612711a6b648c795f565efc8625af66fb57f0c \
+    --hash=sha256:f11327165e5cbb89b2ad1d88d3292b5113332c43b8553b494da435d6ec6f5053
+    # via paramiko
+ipykernel==7.3.0 \
+    --hash=sha256:897eb64da762549ef610698fca5e9675195ec6ac8ec7f19d81ce1ca20c876057 \
+    --hash=sha256:9acaaaf97d16355166e4085afe9d225bfbdf2b7ef520f9df3be8f2b248275e09
+    # via fuse-med-ml
+ipython==9.16.1 \
+    --hash=sha256:4acae635506f6d352d94c4899a19d5f85f8bc4d230932342dca556fdab1c69b4 \
+    --hash=sha256:5a3d1f9a47ff216d6cf9cf863124f6a2c1a198d1354c546a4d24a370a283b64c
+    # via
+    #   fuse-med-ml
+    #   ipykernel
+ipython-pygments-lexers==1.1.1 \
+    --hash=sha256:09c0138009e56b6854f9535736f4171d855c8c08a563a0dcd8022f78355c7e81 \
+    --hash=sha256:a9462224a505ade19a605f71f8fa63c2048833ce50abc86768a0d81d876dc81c
+    # via ipython
+jedi==0.20.0 \
+    --hash=sha256:7bdd9c2634f56713299976f4cbd59cb3fa92165cc5e05ea811fb253480728b67 \
+    --hash=sha256:c3f4ccbd276696f4b19c54618d4fb18f9fc24b0aef02acf704b23f487daa1011
+    # via ipython
 jinja2==3.1.6 \
     --hash=sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d \
     --hash=sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67
@@ -1011,6 +1294,7 @@ jsonargparse==4.50.0 \
     --hash=sha256:b066f0d716767c77b9af58d7e9bb433c42135bd3ea2a4f12e04d6152f4cdf91f \
     --hash=sha256:c559a3991e66cf04d987899b5c1ec6a3de6dc544c44a7cad97cc4a4343066d9a
     # via
+    #   fuse-med-ml
     #   terrakit
     #   terratorch
     #   torchgeo
@@ -1028,6 +1312,20 @@ jsonschema-specifications==2025.9.1 \
     --hash=sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe \
     --hash=sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d
     # via jsonschema
+jupyter-client==8.9.1 \
+    --hash=sha256:0b7a295bc46e8751e9adae84781f726c851c1d911bd793edc4a3bde942e3da81 \
+    --hash=sha256:a58f730dd9e728ba16ba1d62ebccf7ffe1ebbdbce4e95cfae941b7321ae1f4fa
+    # via ipykernel
+jupyter-core==5.9.1 \
+    --hash=sha256:4d09aaff303b9566c3ce657f580bd089ff5c91f5f89cf7d8846c3cdf465b5508 \
+    --hash=sha256:ebf87fdc6073d142e114c72c9e29a9d7ca03fad818c5d300ce2adc1fb0743407
+    # via
+    #   ipykernel
+    #   jupyter-client
+keras==3.15.1 \
+    --hash=sha256:836460e480930acbd19bb7a17e62f9ecad40e8a9af9a651fc8d0586a96d27e20 \
+    --hash=sha256:92ae7c1dd7f61041953dc2d42253181ee099086f0b58ae36fcf98147a6f08a29
+    # via tensorflow
 kiwisolver==1.5.0 \
     --hash=sha256:0b85aad90cea8ac6797a53b5d5f2e967334fa4d1149f031c4537569972596cb8 \
     --hash=sha256:0bf3acf1419fa93064a4c2189ac0b58e3be7872bf6ee6177b0d4c63dc4cea276 \
@@ -1115,6 +1413,22 @@ legacy-api-wrap==1.5 \
     # via
     #   anndata
     #   scanpy
+libclang==18.1.1 \
+    --hash=sha256:0b2e143f0fac830156feb56f9231ff8338c20aecfe72b4ffe96f19e5a1dbb69a \
+    --hash=sha256:3f0e1f49f04d3cd198985fea0511576b0aee16f9ff0e0f0cad7f9c57ec3c20e8 \
+    --hash=sha256:4dd2d3b82fab35e2bf9ca717d7b63ac990a3519c7e312f19fa8e86dcc712f7fb \
+    --hash=sha256:54dda940a4a0491a9d1532bf071ea3ef26e6dbaf03b5000ed94dd7174e8f9592 \
+    --hash=sha256:69f8eb8f65c279e765ffd28aaa7e9e364c776c17618af8bff22a8df58677ff4f \
+    --hash=sha256:6f14c3f194704e5d09769108f03185fce7acaf1d1ae4bbb2f30a72c2400cb7c5 \
+    --hash=sha256:83ce5045d101b669ac38e6da8e58765f12da2d3aafb3b9b98d88b286a60964d8 \
+    --hash=sha256:a1214966d08d73d971287fc3ead8dfaf82eb07fb197680d8b3859dbbbbf78250 \
+    --hash=sha256:c533091d8a3bbf7460a00cb6c1a71da93bffe148f172c7d03b1c31fbf8aa2a0b \
+    --hash=sha256:cf4a99b05376513717ab5d82a0db832c56ccea4fd61a69dbb7bccf2dfb207dbe
+    # via tensorflow
+lifelines==0.30.3 \
+    --hash=sha256:44802480a28d6cb836c7fea4a54ec0ba220eb31c6d7444589637a8bd66066e8c \
+    --hash=sha256:acd1e0ecada4280c7bb2948f39c760a0f9158a57d752c8ca29f984a86c698b7f
+    # via fuse-med-ml
 lightly==1.5.22 \
     --hash=sha256:58694433dd85ec371cb532dba3fea9465009d36e4afac67e53dbf464dba69e2a \
     --hash=sha256:7bb8939976ea5e8fabb20d049812700d51e44f6461f15510a784afd1252a3dbd
@@ -1178,7 +1492,9 @@ locket==1.0.0 \
 loguru==0.7.3 \
     --hash=sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6 \
     --hash=sha256:31a33c10c8e1e10422bfd431aeb5d351c7cf7fa671e3c4df004162264b28220c
-    # via compressed-tensors
+    # via
+    #   compressed-tensors
+    #   x-transformers
 markdown==3.10.3 \
     --hash=sha256:3589362618f743188b4d955b874402bc814f4f83f544dc207719f4baa7d9c45f \
     --hash=sha256:fa6c92a00a4a3c98b22728c64a935ae1928250ae65058a6ded814d2cc29a4cea
@@ -1255,9 +1571,17 @@ matplotlib==3.11.1 \
     # via
     #   captum
     #   contextily
+    #   fuse-med-ml
+    #   lifelines
     #   scanpy
     #   seaborn
     #   torchgeo
+matplotlib-inline==0.2.2 \
+    --hash=sha256:3c821cf1c209f59fb2d2d64abbf5b23b67bcb2210d663f9918dd851c6da1fcf6 \
+    --hash=sha256:72f3fe8fce36b70d4a5b612f899090cd0401deddc4ea90e1572b9f4bfb058c79
+    # via
+    #   ipykernel
+    #   ipython
 mcp==1.19.0 \
     --hash=sha256:213de0d3cd63f71bc08ffe9cc8d4409cc87acffd383f6195d2ce0457c021b5c1 \
     --hash=sha256:f5907fe1c0167255f916718f376d05f09a830a215327a3ccdd5ec8a519f2e572
@@ -1291,7 +1615,10 @@ ml-dtypes==0.5.4 \
     --hash=sha256:cb73dccfc991691c444acc8c0012bee8f2470da826a92e3a20bb333b1a7894e6 \
     --hash=sha256:ce756d3a10d0c4067172804c9cc276ba9cc0ff47af9078ad439b075d1abdc29b \
     --hash=sha256:f21c9219ef48ca5ee78402d5cc831bd58ea27ce89beda894428bc67a52da5328
-    # via tilelang
+    # via
+    #   keras
+    #   tensorflow
+    #   tilelang
 model-hosting-container-standards==0.1.16 \
     --hash=sha256:47f4f65713120bc3a69feb022981a38db9e557aedf88dbd72077f20588caa12b \
     --hash=sha256:d34589633900e53c3ee5f7c78280a7cf7e4f6532c35e763341a262fc85cbe84a
@@ -1304,6 +1631,31 @@ mpmath==1.3.0 \
     --hash=sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f \
     --hash=sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c
     # via sympy
+msgpack==1.2.1 \
+    --hash=sha256:020e881a764b20d8d7ca1a54fc01b8175519d108e3c3f194fddc200bda95951a \
+    --hash=sha256:04c721c2c7448767e9e3f2520a475663d8ee0f09c31890f6d2bd70fd636a9647 \
+    --hash=sha256:0a70e3cf2804a300d921bb0940426e35f4e489a23adfb77a808892241db0a064 \
+    --hash=sha256:0c0d9802354507bcba62af19c17918e3eb437cc25e6f50657d511b5856a77aac \
+    --hash=sha256:1233ee2dd0cefba127583de50ea654677277047d238303521db35def3d7b2e7c \
+    --hash=sha256:2ef59c659f289eddf8aa6623823f19fa2f40a4029266889eac7a2505dd210c35 \
+    --hash=sha256:33f14fba63278b714efe6ad07e50ea5f03d91537aa6a1c5f1ceca4cf44013ca9 \
+    --hash=sha256:4202c74688ca06591f78cb18988228bd4cca2cc75d57b60008372892d2f1e6e6 \
+    --hash=sha256:4227224aaec8f7fbcbfbd4272319347b2bb4030366502600f8c45588c5187b07 \
+    --hash=sha256:491cc39455ca765fad51fb451bf2915eb2cf41192ab5801ce8d67c1d614fe056 \
+    --hash=sha256:5c24aa15d5963051e1a5c62b12c50cd705992502b5ec1f3bece6046f33c9fc24 \
+    --hash=sha256:60926b75d00c8e816ef98f3034f484a8bc64242d66839cef4cf7e503142316a0 \
+    --hash=sha256:6d09badf350af2be9d189184e04e64cf54ad93569ab3d96fca58bd3e84aad707 \
+    --hash=sha256:787c9bebb5833e8f6fc8abca3c0597683d8d87f56a8842b6b89c75a5f3176e2d \
+    --hash=sha256:85f57e960d877f2977f6430896191b04a21f8901b3b4baf2e4604329f4db5402 \
+    --hash=sha256:8b267ce94efb76fbd1b3373511420074ee3187f0f7811bf394531de13294735a \
+    --hash=sha256:afc5febcd4c99effbc02b528e49d6fd0760b2b7d48c05239e345a5fa6e743d9a \
+    --hash=sha256:d3567748a5107cb40cdf66a275430c2f87c07777698f4bfd25c35f44d533258c \
+    --hash=sha256:dc871b997a9370d855b7394465f2f350e847a5b806dd38dcc9c989e7d87da155 \
+    --hash=sha256:e3dc2feb0876209d9c38aa56cb1de169bd6c4348f1aa48271f241226590993e6 \
+    --hash=sha256:e4f1d0f8f98ade9634e01fb704a408f9336c0a8f1117b369f5db83dc7551d8b1 \
+    --hash=sha256:f02cf17a6ca1abe29b5f980644f7551f94d71f2011509b26d8625ce038f0df64 \
+    --hash=sha256:f310233ef7fb9c14e201c93639fe5f5260b005f56f0b29048e999c30935596cc
+    # via blosc2
 msgspec==0.21.1 \
     --hash=sha256:21995e74b5c598c2e004110ad66ec7f1b8c20bf2bcf3b2de8fd9a3094422d3ff \
     --hash=sha256:2313508e394b0d208f8f56892ca9b2799e2561329de9763b19619595a6c0f72c \
@@ -1392,20 +1744,57 @@ mypy-extensions==1.1.0 \
     --hash=sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505 \
     --hash=sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558
     # via typing-inspect
+namex==0.1.0 \
+    --hash=sha256:117f03ccd302cc48e3f5c58a296838f6b89c83455ab8683a1e85f2a430aa4306 \
+    --hash=sha256:e2012a474502f1e2251267062aae3114611f07df4224b6e06334c57b0f2ce87c
+    # via keras
 narwhals==2.24.0 \
     --hash=sha256:42fdedf44e5b2ca7505630d45b4ac3058f38d8485cba9fe1652ca23152df7489 \
     --hash=sha256:b5c0f684ccd9d7475b564111e319a4964abcf2baf79d3cf6b1003d06ac9b828d
-    # via scikit-learn
+    # via
+    #   formulaic
+    #   scikit-learn
 natsort==8.4.0 \
     --hash=sha256:45312c4a0e5507593da193dedd04abb1469253b601ecaf63445ad80f0a1ea581 \
     --hash=sha256:4732914fb471f56b5cce04d7bae6f164a592c7712e1c85f9ef585e197299521c
     # via
     #   anndata
     #   scanpy
+ndindex==1.10.1 \
+    --hash=sha256:03cf1e6cdac876bd8fc92d3b65bb223496b1581d10eab3ba113f7c195121a959 \
+    --hash=sha256:046c1e88d46b2bd2fd3483e06d27b4e85132b55bc693f2fca2db0bb56eea1e78 \
+    --hash=sha256:08bfdc1f7a0b408d15b3ce61d141ebbebdb47a25341967e425e104c5bd512a5c \
+    --hash=sha256:0f6113c1f031248f8818cbee1aa92aa3c9472b7701debcce9fddebcd2f610f11 \
+    --hash=sha256:157b5c34a1b779f5d27b790d9bd7e7b156d284e76be83c591a3ba003984f4956 \
+    --hash=sha256:23d35696f802548143b5cc199bf2f171efb0061aa7934959251dd3bae56d038c \
+    --hash=sha256:346a4bf09f5771548665c8206e81daadb6b9925d409746e709894bdd98adc701 \
+    --hash=sha256:3b0d9ce2c8488444499ab6d40e92e09867bf4413f5cf04c01635de923f44aa67 \
+    --hash=sha256:5c026dbbf2455d97ce6456d8a50b349aee8fefa11027d020638c89e9be2c9c4c \
+    --hash=sha256:6928e47fb008903f2e41309b7ff1e59b16abbcd59e2e945454571c28b2433c9e \
+    --hash=sha256:72af787dcee3661f36fff9d144d989aacefe32e2c8b51ceef9babd46afb93a18 \
+    --hash=sha256:752e78a5e87911ded117c57a7246596f26c9c6da066de3c2b533b3db694949bb \
+    --hash=sha256:78bfe25941d2dac406391ddd9baf0b0fce163807b98ecc2c47a3030ee8466319 \
+    --hash=sha256:7da34a78410c14341d5fff73be5ce924bd36500bf7f640fc59b8607d3a0df95e \
+    --hash=sha256:87f83e8c35a7f49a68cd3a3054c406e6c22f8c1315f3905f7a778c657669187e \
+    --hash=sha256:9599fcb7411ffe601c367f0a5d4bc0ed588e3e7d9dc7604bdb32c8f669456b9e \
+    --hash=sha256:a91e1a0398120233d5c3b23ccb2d4b78e970d66136f1a7221fa9a53873c3d5c5 \
+    --hash=sha256:c9dd58d91220b1c1fe516324bfcf4114566c98e84b1cbbe416abe345c75bd557 \
+    --hash=sha256:cb76e0f3f235d8b1c768b17e771de48775d281713795c3aa045e8114ad61bdda \
+    --hash=sha256:cf9e05986b2eb8c5993bce0f911d6cedd15bda30b5e35dd354b1ad1f4cc3599d \
+    --hash=sha256:d0ebdba2fade3f6916fe21fd49e2a0935af4f58c56100a60f3f2eb26e20baee7 \
+    --hash=sha256:e69a2cb1ac7be955c3c77f1def83f410775a81525c9ce2d4c0a3f2a61589ed47 \
+    --hash=sha256:ef3ef22390a892d16286505083ee5b326317b21c255a0c7f744b1290a0b964a6 \
+    --hash=sha256:f99b3e89220da3244d03c9c5473669c7107d361c129fd9b064622744dee1ce15 \
+    --hash=sha256:fa60637dfae1ee3fc057e420a52cc4ace38cf2c0d1a0451af2a3cba84d281842
+    # via blosc2
 nest-asyncio==1.6.0 \
     --hash=sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe \
     --hash=sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c
     # via terrakit
+nest-asyncio2==1.7.2 \
+    --hash=sha256:1921d70b92cc4612c374928d081552efb59b83d91b2b789d935c665fa01729a8 \
+    --hash=sha256:f5dfa702f3f81f6a03857e9a19e2ba578c0946a4ad417b4c50a24d7ba641fe01
+    # via ipykernel
 netcdf4==1.7.4 \
     --hash=sha256:75cf59100f0775bc4d6b9d4aca7cbabd12e2b8cf3b9a4fb16d810b92743a315a \
     --hash=sha256:876ad9d58f09c98741c066c726164c45a098a58fb90e5fac9e74de4bb8a793fd \
@@ -1423,6 +1812,10 @@ networkx==3.6.1 \
     #   scanpy
     #   scikit-image
     #   torch
+nibabel==5.4.2 \
+    --hash=sha256:553482c5f1e1034fc312edf6fb7f32236c0056439845d1c29293b7e8c98d4854 \
+    --hash=sha256:d5f4b9076a13178ae7f7acf18c8dbd503ee1c4d5c0c23b85df7be87efcbb49da
+    # via fuse-med-ml
 ninja==1.13.0 \
     --hash=sha256:11be2d22027bde06f14c343f01d31446747dbb51e72d00decca2eb99be911e2f \
     --hash=sha256:1c97223cdda0417f414bf864cfb73b72d8777e57ebb279c5f6de368de0062988 \
@@ -1495,7 +1888,10 @@ numexpr==2.14.2 \
     --hash=sha256:dd905922d7dce457947d54b84c7ac345cef37332b724445e159a5a1a2080ce2b \
     --hash=sha256:e7144e83ea9e581f2273e0304f15836736c4e470e2bd2e378ce617662a1ca278 \
     --hash=sha256:fd2f5882a66a7792aa6614c68831aa20085b499d41422aedd001080624ebb14c
-    # via bmfm-targets
+    # via
+    #   blosc2
+    #   bmfm-targets
+    #   tables
 numpy==2.3.5 ; python_full_version < '3.13' \
     --hash=sha256:00dc4e846108a382c5869e77c6ed514394bdeb3403461d25a829711041217d5b \
     --hash=sha256:0472f11f6ec23a74a906a00b48a4dcf3849209696dff7c189714511268d103ae \
@@ -1536,23 +1932,31 @@ numpy==2.3.5 ; python_full_version < '3.13' \
     #   albucore
     #   albumentations
     #   anndata
+    #   autograd
+    #   blosc2
     #   bmfm-targets
     #   captum
     #   cellxgene-census
     #   cftime
+    #   choix
     #   clearml
     #   contourpy
     #   cuda-core
     #   dask
     #   diffusers
+    #   einx
     #   fast-array-utils
     #   flashinfer-python
     #   focal-loss-torch
     #   folium
+    #   formulaic
+    #   fuse-med-ml
     #   geopandas
     #   h5py
     #   humming-kernels
     #   imageio
+    #   keras
+    #   lifelines
     #   lightly
     #   lightly-utils
     #   litdata
@@ -1560,6 +1964,7 @@ numpy==2.3.5 ; python_full_version < '3.13' \
     #   mistral-common
     #   ml-dtypes
     #   netcdf4
+    #   nibabel
     #   numba
     #   numcodecs
     #   numexpr
@@ -1589,8 +1994,10 @@ numpy==2.3.5 ; python_full_version < '3.13' \
     #   somacore
     #   stackstac
     #   statsmodels
+    #   tables
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   terrakit
     #   terratorch
     #   tifffile
@@ -1646,23 +2053,31 @@ numpy==2.4.6 ; python_full_version >= '3.13' \
     #   albucore
     #   albumentations
     #   anndata
+    #   autograd
+    #   blosc2
     #   bmfm-targets
     #   captum
     #   cellxgene-census
     #   cftime
+    #   choix
     #   clearml
     #   contourpy
     #   cuda-core
     #   dask
     #   diffusers
+    #   einx
     #   fast-array-utils
     #   flashinfer-python
     #   focal-loss-torch
     #   folium
+    #   formulaic
+    #   fuse-med-ml
     #   geopandas
     #   h5py
     #   humming-kernels
     #   imageio
+    #   keras
+    #   lifelines
     #   lightly
     #   lightly-utils
     #   litdata
@@ -1670,6 +2085,7 @@ numpy==2.4.6 ; python_full_version >= '3.13' \
     #   mistral-common
     #   ml-dtypes
     #   netcdf4
+    #   nibabel
     #   numba
     #   numcodecs
     #   numexpr
@@ -1699,8 +2115,10 @@ numpy==2.4.6 ; python_full_version >= '3.13' \
     #   somacore
     #   stackstac
     #   statsmodels
+    #   tables
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   terrakit
     #   terratorch
     #   tifffile
@@ -1765,9 +2183,7 @@ nvidia-cuda-nvrtc==13.3.33 ; sys_platform == 'darwin' \
     --hash=sha256:7b05ecda494c6dabc44231a608b060a71008a730d9dfda932cc508e6d29159e0 \
     --hash=sha256:7d2af818851c0c224d5f92221e9226e51ee23c236df4b51f9194563979c888be \
     --hash=sha256:82530788b8c6164a54d3fd9ae8bcca8893d397c4aeb998861982a03bbe41e204
-    # via
-    #   humming-kernels
-    #   nvidia-cublas
+    # via humming-kernels
 nvidia-cuda-runtime==13.0.96 ; sys_platform != 'darwin' \
     --hash=sha256:7f82250d7782aa23b6cfe765ecc7db554bd3c2870c43f3d1821f1d18aebf0548 \
     --hash=sha256:ef9bcbe90493a2b9d810e43d249adb3d02e98dd30200d86607d8d02687c43f55 \
@@ -1934,6 +2350,7 @@ omegaconf==2.3.1 \
     --hash=sha256:e5e7de64aeebeddaf8e6d3f7a783b32ac2a01c0fbd9c878012caecb891a1f42a
     # via
     #   bmfm-targets
+    #   fuse-med-ml
     #   hydra-core
 openai==2.53.0 \
     --hash=sha256:baf5802ad08980e1d9d561e1b996e800c8bcd14af5847c6d0e7a5cc59e4d4116 \
@@ -2023,10 +2440,57 @@ opentelemetry-semantic-conventions-ai==0.5.1 \
     --hash=sha256:153906200d8c1d2f8e09bd78dbef526916023de85ac3dab35912bfafb69ff04c \
     --hash=sha256:25aeb22bd261543b4898a73824026d96770e5351209c7d07a0b1314762b1f6e4
     # via vllm
+opt-einsum==3.4.0 \
+    --hash=sha256:69bb92469f86a1565195ece4ac0323943e83477171b91d24c35afe028a90d7cd \
+    --hash=sha256:96ca72f1b886d148241348783498194c577fa30a8faac108586b14f1ba4473ac
+    # via tensorflow
+optree==0.19.1 \
+    --hash=sha256:03faa8e23fdaf3a18f9a1568c2c0eb0641a6aa05baf3a20639bd11fb34664700 \
+    --hash=sha256:06f5c8a4cf356a1a276ce5cec1be44719ed260690f79c036d04b4d427e801258 \
+    --hash=sha256:08ccec0ee5a565eb5aa4fe30383016a358627ea23d968ec8ab28b1f2ce4ce3d8 \
+    --hash=sha256:1c5d21176b670407f4555aae40711668832599c4fb0627000c5ce3ed0d6e2dae \
+    --hash=sha256:39a006735d2a0a68751a3bc33d670184fddcd86db63b0293e1e819739e8105e4 \
+    --hash=sha256:4497d1c9197b8c6842e511368163d318ce536521ebdcff8bebb7551dcdfac532 \
+    --hash=sha256:544b70958dbd7e732bc6874e0180c609c9052115937d0ec28123bb49c1a574aa \
+    --hash=sha256:5d9d198343e1e6ced18bef0cbff84091c1877964fc4a121df33f18840e073a01 \
+    --hash=sha256:672588408906051d3e9a99aca6c0af93c6e0b638137a701418088eaa0bb6c719 \
+    --hash=sha256:6f0b1efc177bed6495f78d39d5aa495ccb31cc20bcf64bb1b806ca4c919f4049 \
+    --hash=sha256:76b3e9e5d37e6b05ec82fff91758c8c0e27e159b35faea4b33d5eb975d720257 \
+    --hash=sha256:7a1202371d9fe3aa75f3e886b1f871aac4991a655aadb65e54f58a3ae9388ab2 \
+    --hash=sha256:7d934f240b109c6891dd06b2e30400b123b8a4b6ed31dcd0db2ae2378d30a6e8 \
+    --hash=sha256:9690c132822d9dee479cf7dff8cc52a67c8af42a4f7529d21f0f4f1d99e4c84e \
+    --hash=sha256:96e5c7c3b9144f08ae40c3d9848cfbcfa36b6bead0f8215ad071d5922ee6c4a5 \
+    --hash=sha256:9870d33ec50cca0c46c2b431cea24c6247457da15fd4ad66ccb8ab78145c1490 \
+    --hash=sha256:9dde5b756946c1f1458aeab248a7a9b0c01bb06b5787de9f06d52ad38b745557 \
+    --hash=sha256:a33bd23fc5c67ecb9ff491b75fde10cd9b53f47f8a876de842090e8c7a2437e1 \
+    --hash=sha256:a9b9c7e9148ec470124dc4c1d1cd1485dbeb35973357b5911b181a79090426d2 \
+    --hash=sha256:aa0845b725bcd0029e179cf9b4bc2cc016c7358e56fc7c0d2c43bf4d514c96cf \
+    --hash=sha256:ab8ad9803376d553a2958471b6bb6842b7e15888e19cc6aeb76da96c6afd948d \
+    --hash=sha256:afd4abeb2783b2367093287bc6268ac9af244b20c8d9b01696ccfe817483b66c \
+    --hash=sha256:b9120510d3f951e268e417a3f64f335bc1c539e1e80bff2129ddc6fb60ac7b56 \
+    --hash=sha256:b964bcdb5cfe367cdf56447e80ba5a49123098d8c4e8e68b41c20890eec6e58e \
+    --hash=sha256:d16cef4d0555d49ce221d80249f1285a2d3faf932e451c3ce6cb8ccb6a846767 \
+    --hash=sha256:d2cb43c36638f469f5d8f4cf638e914de90c62242d8bed29f1b4487e0346ab94 \
+    --hash=sha256:d41ccc4c20bfeae01d1d221c057a6d026e84e32229664952eddcdbe4b9b71417 \
+    --hash=sha256:dc2db0b449baff53aa7e583306101de0ade5e5ae9e6fce78400eb2319bbd23dc \
+    --hash=sha256:ddeefb7ca799c09647e332ebc1a5f6c09888a5a0e51f2dff4ca55e65b42a8c14 \
+    --hash=sha256:e0f02600832ab8d0f6c934dcb5c339e17a36938d477641a45798e02625ebe107 \
+    --hash=sha256:e70faa00ab69331f49f8337d45021bed09ae2265d1db72eea9d7817af2b73c64 \
+    --hash=sha256:e757079d44a00319447f43df5c51e55bf9b62d9f05eea0e2db5ff7c7ca5ec71d \
+    --hash=sha256:f0ce49f64f804f7f35f2f9c2a21e3ba94c090199fccdcfd40e3ded4426c5c175 \
+    --hash=sha256:f10d58c1a17e1b32f9d9b5e1b9d1ad964d99c1113d9df0b9f62f2fe7dde19909 \
+    --hash=sha256:f144cfd65fb17c6aa2c51818614eb009e6052d3d6ace91f7e570b1318cdcac4c \
+    --hash=sha256:f1d7838e8b1b62258abd73a5911afad1153ed76822070558c3ba7e0bb5b44192 \
+    --hash=sha256:f658fa46305b2bdccdc5bb2cb07818aeaef88a1085499deda5be48a0a58d2971
+    # via keras
 orderedmultidict==1.0.2 \
     --hash=sha256:16a7ae8432e02cc987d2d6d5af2df5938258f87c870675c73ee77a0920e6f4a6 \
     --hash=sha256:ab5044c1dca4226ae4c28524cfc5cc4c939f0b49e978efa46a6ad6468049f79b
     # via furl
+orderly-set==5.5.0 \
+    --hash=sha256:46f0b801948e98f427b412fcabb831677194c05c3b699b80de260374baa0b1e7 \
+    --hash=sha256:e87185c8e4d8afa64e7f8160ee2c542a475b738bc891dc3f58102e654125e6ce
+    # via deepdiff
 outlines-core==0.2.14 \
     --hash=sha256:0e4c69f0a8565edb56464c4c9b6c291a10805f3a96dff84182980e90ae1a5e2f \
     --hash=sha256:1de34681c7e0e7e1551fc9036e4fa3c57986336c905a10536591ceb6d869c258 \
@@ -2058,6 +2522,8 @@ packaging==26.3 \
     #   geopandas
     #   huggingface-hub
     #   hydra-core
+    #   ipykernel
+    #   keras
     #   kornia
     #   lazy-loader
     #   lightning
@@ -2065,20 +2531,26 @@ packaging==26.3 \
     #   lm-format-enforcer
     #   marshmallow
     #   matplotlib
+    #   nibabel
     #   pandera
     #   peft
     #   pyogrio
+    #   pytest
     #   pytorch-lightning
     #   rioxarray
     #   scanpy
     #   scikit-image
     #   statsmodels
+    #   tables
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   tiledb
     #   tiledb-cloud
     #   torchmetrics
     #   transformers
+    #   wheel
+    #   x-transformers
     #   xarray
     #   zarr
 pandas==2.3.3 \
@@ -2106,7 +2578,10 @@ pandas==2.3.3 \
     # via
     #   anndata
     #   bmfm-targets
+    #   formulaic
+    #   fuse-med-ml
     #   geopandas
+    #   lifelines
     #   rdata
     #   rnanorm
     #   scanpy
@@ -2122,6 +2597,14 @@ pandera==0.32.1 \
     --hash=sha256:1a17a3ffa906174d19207715f4f082ec3db3709647927ad8c095c147d74d8454 \
     --hash=sha256:72ecd74226847abf0f0437c05f7f10cc8368e306d88a2acc78fa93762c5a0a02
     # via rnanorm
+paramiko==5.0.0 \
+    --hash=sha256:36763b5b95c2a0dcfdf1abc48e48156ee425b21efe2f0e787c2dd5a95c0e5e79 \
+    --hash=sha256:b7044611c30140d9a75261653210e2002977b71a0497ff3ba0d98d7edbf62f7c
+    # via fuse-med-ml
+parso==0.8.7 \
+    --hash=sha256:a8926eb2a1b915486941fdbd31e86a4baf88fe8c210f25f2f35ecec5b574ca1c \
+    --hash=sha256:eaaac4c9fdd5e9e8852dc778d2d7405897ec510f2a298071453e5e3a07914bb1
+    # via jedi
 partd==1.4.2 \
     --hash=sha256:978e4ac767ec4ba5b86c6eaa52e5a2a3bc748a2ca839e8cc798f1cc6ce6efb0f \
     --hash=sha256:d022c33afbdc8405c226621b015e8067888173d85f7f5ecebb3cafed9a20f02c
@@ -2143,7 +2626,13 @@ patsy==1.0.2 \
 peft==0.20.0 \
     --hash=sha256:0fbba16ffebfad3de96e06f2da6860fd860292324b85b6141909fa1e26ea9233 \
     --hash=sha256:4769c8093a4ca145fd6fb3fd4dd50449675f5fe46434ad1e98b285a132d4b1d0
-    # via bmfm-targets
+    # via
+    #   biomed-multi-alignment
+    #   bmfm-targets
+pexpect==4.9.0 ; sys_platform != 'emscripten' and sys_platform != 'win32' \
+    --hash=sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 \
+    --hash=sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f
+    # via ipython
 pillow==12.3.0 \
     --hash=sha256:0847a763afefb695bc912d7c131e7e0632d4edc1d8698f58ddabec8e46b8b6d3 \
     --hash=sha256:0dd2064cbc55aaec028ef5fbb60fa47bb6c3e7918e07ff17935284b227a9d2df \
@@ -2186,7 +2675,13 @@ pillow==12.3.0 \
 platformdirs==4.11.0 \
     --hash=sha256:0555d18370482847566ffabcaa53ad7c6c1c29f195989ae1ed634a05f76ea1e0 \
     --hash=sha256:360ccded2b7fce0af0ff80cc8f5942a1c5d99b0e856033acb030bfc634709e74
-    # via tacoreader
+    # via
+    #   jupyter-core
+    #   tacoreader
+pluggy==1.6.0 \
+    --hash=sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3 \
+    --hash=sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746
+    # via pytest
 prometheus-client==0.26.0 \
     --hash=sha256:04a91bcf94e2cf74a44a1a874d651a2e853ed354b6e822f3b7487751465d5c2b \
     --hash=sha256:fa93d06737aa02bacd05794768508bb97d2fbee28cb3bca04eaae92f0ca953d6
@@ -2197,6 +2692,10 @@ prometheus-fastapi-instrumentator==8.1.0 \
     --hash=sha256:b77f3043665e8d28e2bbd21017506195a43d9adf1d402d01bf95b494b7e560e1 \
     --hash=sha256:b9f40b2cff3f7891ca0610b3ae4fc6ec723fd326b04bb659819aaeb821a0fc7d
     # via vllm
+prompt-toolkit==3.0.53 \
+    --hash=sha256:01c0891d7f9237d5e339f7d3e42cdae80b7534abb1c7c0e3352efba6231492f2 \
+    --hash=sha256:9ec8a0ad96d5c56148b3f914aa79c1564c3fde5d2e6b876e7bc327e353cf8fa6
+    # via ipython
 propcache==0.5.2 \
     --hash=sha256:01c4fc7480cd0598bb4b57022df55b9ca296da7fc5a8760bd8451a7e63a7d427 \
     --hash=sha256:06187263ddad280d05b4d8a8b3bb7d164cbebd469236544a42e6d9b28ac6a4fa \
@@ -2272,6 +2771,7 @@ protobuf==6.33.6 \
     #   opentelemetry-proto
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   vllm
 psutil==7.2.2 \
     --hash=sha256:0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372 \
@@ -2293,13 +2793,26 @@ psutil==7.2.2 \
     #   accelerate
     #   cellxgene-census
     #   clearml
+    #   fuse-med-ml
+    #   ipykernel
+    #   ipython
     #   peft
     #   tilelang
     #   vllm
+ptyprocess==0.7.0 ; sys_platform != 'emscripten' and sys_platform != 'win32' \
+    --hash=sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35 \
+    --hash=sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220
+    # via pexpect
+pure-eval==0.2.3 \
+    --hash=sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0 \
+    --hash=sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42
+    # via stack-data
 py-cpuinfo==9.0.0 \
     --hash=sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690 \
     --hash=sha256:859625bc251f64e21f077d099d4162689c762b5d6a4c3c97553d56241c9674d5
-    # via vllm
+    # via
+    #   tables
+    #   vllm
 pyarrow==25.0.0 \
     --hash=sha256:0721332c30fdd453fdd1fc203b2ac1f4c9db5aea28fa38d41f2574c4b068b9ec \
     --hash=sha256:149730a3d1f0fb59d663a0b8aa210adfd9c17c27cd94a0d143e60daea8320d4e \
@@ -2422,12 +2935,14 @@ pycocotools==2.0.11 \
     --hash=sha256:f7eb43b79448476b094240450420b7425d06e297880144b8ea6f01e9b4340e43 \
     --hash=sha256:fd72b9734e6084b217c1fc3945bfd4ec05bdc75a44e4f0c461a91442bb804973 \
     --hash=sha256:ffe806ce535f5996445188f9a35643791dc54beabc61bd81e2b03367356d604f
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   terratorch
 pycountry==26.2.16 \
     --hash=sha256:115c4baf7cceaa30f59a4694d79483c9167dbce7a9de4d3d571c5f3ea77c305a \
     --hash=sha256:5b6027d453fcd6060112b951dd010f01f168b51b4bf8a1f1fc8c95c8d94a0801
     # via pydantic-extra-types
-pycparser==3.0 ; implementation_name == 'pypy' \
+pycparser==3.0 ; (implementation_name != 'PyPy' and platform_python_implementation != 'PyPy') or (implementation_name == 'pypy' and platform_python_implementation == 'PyPy') \
     --hash=sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29 \
     --hash=sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992
     # via cffi
@@ -2437,6 +2952,7 @@ pydantic==2.13.4 \
     # via
     #   albumentations
     #   anthropic
+    #   blosc2
     #   bmfm-targets
     #   compressed-tensors
     #   fastapi
@@ -2514,11 +3030,30 @@ pyelftools==0.33 \
 pygments==2.20.0 \
     --hash=sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f \
     --hash=sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176
-    # via rich
+    # via
+    #   ipython
+    #   ipython-pygments-lexers
+    #   pytest
+    #   rich
 pyjwt==2.9.0 \
     --hash=sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850 \
     --hash=sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c
     # via clearml
+pynacl==1.6.2 \
+    --hash=sha256:018494d6d696ae03c7e656e5e74cdfd8ea1326962cc401bcf018f1ed8436811c \
+    --hash=sha256:22de65bb9010a725b0dac248f353bb072969c94fa8d6b1f34b87d7953cf7bbe4 \
+    --hash=sha256:26bfcd00dcf2cf160f122186af731ae30ab120c18e8375684ec2670dccd28130 \
+    --hash=sha256:46065496ab748469cdd999246d17e301b2c24ae2fdf739132e580a0e94c94a87 \
+    --hash=sha256:5811c72b473b2f38f7e2a3dc4f8642e3a3e9b5e7317266e4ced1fba85cae41aa \
+    --hash=sha256:62985f233210dee6548c223301b6c25440852e13d59a8b81490203c3227c5ba0 \
+    --hash=sha256:68be3a09455743ff9505491220b64440ced8973fe930f270c8e07ccfa25b1f9e \
+    --hash=sha256:834a43af110f743a754448463e8fd61259cd4ab5bbedcf70f9dabad1d28a394c \
+    --hash=sha256:8845c0631c0be43abdd865511c41eab235e0be69c81dc66a50911594198679b0 \
+    --hash=sha256:8a66d6fb6ae7661c58995f9c6435bda2b1e68b54b598a6a10247bfcdadac996c \
+    --hash=sha256:8b097553b380236d51ed11356c953bf8ce36a29a3e596e934ecabe76c985a577 \
+    --hash=sha256:c8a231e36ec2cab018c4ad4358c386e36eede0319a0c41fed24f840b1dac59f6 \
+    --hash=sha256:c949ea47e4206af7c8f604b8278093b674f7c79ed0d4719cc836902bf4517465
+    # via paramiko
 pynndescent==0.6.0 \
     --hash=sha256:7ffde0fb5b400741e055a9f7d377e3702e02250616834231f6c209e39aac24f5 \
     --hash=sha256:dc8c74844e4c7f5cbd1e0cd6909da86fdc789e6ff4997336e344779c3d5538ef
@@ -2724,6 +3259,10 @@ pystac-ext-xarray-assets==1.0.0 \
     --hash=sha256:a31e90e7e9bc5ae191e7449df28c39857c818e8c1cf2c09a2eceaa7c6e13241c \
     --hash=sha256:da4f4877c018d531b6b5c45f20bc64842f14587ae86bac8d2acf110804c773d1
     # via pystac
+pytest==9.1.1 \
+    --hash=sha256:1088fbde8f2b49d95a549a195707afa7a76a3ce9bcadc26b6d71f0ffda5fe313 \
+    --hash=sha256:37a86b45efb9a47a61a36449063e8e18d0cab3161329fc099eb21783169c4f0c
+    # via biomed-multi-alignment
 python-box==7.4.1 \
     --hash=sha256:2ca9a18fd15326bc267e9cc7e0e6e3a0cb78d11507940f43f687adf7e156d882 \
     --hash=sha256:615da3fafd41572aec1b905832555c0ea08b6fbc27cc917356e257a9a5721af7 \
@@ -2741,6 +3280,7 @@ python-dateutil==2.9.0.post0 \
     #   aiobotocore
     #   botocore
     #   clearml
+    #   jupyter-client
     #   lightly
     #   matplotlib
     #   multiurl
@@ -2772,6 +3312,7 @@ pytorch-lightning==2.6.5 \
     --hash=sha256:62d9c8549b2278fedc3364f0a5607a56c6063d18635008f8cf3fae8d802b0d76
     # via
     #   bmfm-targets
+    #   fuse-med-ml
     #   lightly
     #   lightning
 pytz==2026.3.post1 \
@@ -2851,7 +3392,10 @@ pyzmq==27.1.0 \
     --hash=sha256:e343d067f7b151cfe4eb3bb796a7752c9d369eed007b91231e817071d2c2fec7 \
     --hash=sha256:f30f395a9e6fbca195400ce833c731e7b64c3919aa481af4d88c3759e0cb7496 \
     --hash=sha256:fbb4f2400bfda24f12f009cba62ad5734148569ff4949b1b6ec3b519444342e6
-    # via vllm
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   vllm
 quack-kernels==0.6.1 \
     --hash=sha256:266705ea82117e9b1c8a9e44d68a458519f2498d966c0efffd6812120c3995ad \
     --hash=sha256:a694f89c91d137478de523c0227365a331ac9cb66790cfb08baa3dbfaafc71e7
@@ -2969,6 +3513,7 @@ requests==2.34.2 \
     #   pystac-client
     #   requests-oauthlib
     #   sentinelhub
+    #   tensorflow
     #   terrakit
     #   tiktoken
     #   torchdata
@@ -2981,7 +3526,9 @@ rich==15.0.0 \
     --hash=sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb \
     --hash=sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36
     # via
+    #   blosc2
     #   bmfm-targets
+    #   keras
     #   rich-toolkit
     #   terratorch
     #   typer
@@ -3157,6 +3704,7 @@ scikit-learn==1.9.0 \
     --hash=sha256:da76d09304a4706db7cc1e3ebaa3b6b98a67365cc11d2996c4f1e58ba47df714
     # via
     #   cellxgene-census
+    #   fuse-med-ml
     #   pynndescent
     #   rnanorm
     #   scanpy
@@ -3200,8 +3748,13 @@ scipy==1.18.0 \
     # via
     #   albumentations
     #   anndata
+    #   autograd-gamma
     #   bmfm-targets
+    #   choix
     #   fast-array-utils
+    #   formulaic
+    #   fuse-med-ml
+    #   lifelines
     #   pynndescent
     #   rioxarray
     #   scanpy
@@ -3304,6 +3857,7 @@ setuptools==80.10.2 \
     # via
     #   model-hosting-container-standards
     #   tensorboard
+    #   tensorflow
     #   tilelang
     #   torch
     #   vllm
@@ -3381,12 +3935,15 @@ six==1.17.0 \
     --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
     --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
     # via
+    #   astunparse
     #   clearml
     #   furl
+    #   google-pasta
     #   lightly
     #   orderedmultidict
     #   pathlib2
     #   python-dateutil
+    #   tensorflow
     #   tiledb-cloud
     #   vllm
 sniffio==1.3.1 \
@@ -3403,6 +3960,10 @@ sse-starlette==3.4.8 \
     --hash=sha256:6e82314c786709a3cd9520f2285cf9fff90e181e598e8a357b0cf80f66afba0d \
     --hash=sha256:ed89ffbb75cbf78a5fe2f2109cd584792ee7f9dfac96f791db546df8f15f3f9c
     # via mcp
+stack-data==0.6.3 \
+    --hash=sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9 \
+    --hash=sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695
+    # via ipython
 stackstac==0.5.1 \
     --hash=sha256:1af0e1251100fe506b1f3c035ffcc34111ad67b264275d14a6775c4991e5f7f6 \
     --hash=sha256:3c596c9ccf502b6230b1c9e970a8099eeb94df867d0dea2fd45071223cb581e7
@@ -3431,7 +3992,9 @@ statsmodels==0.14.6 \
     --hash=sha256:d8c00a42863e4f4733ac9d078bbfad816249c01451740e6f5053ecc7db6d6368 \
     --hash=sha256:f1c08befa85e93acc992b72a390ddb7bd876190f1360e61d10cf43833463bc9c \
     --hash=sha256:fe76140ae7adc5ff0e60a3f0d56f4fffef484efa803c3efebf2fcd734d72ecb5
-    # via scanpy
+    # via
+    #   fuse-med-ml
+    #   scanpy
 stringzilla==5.0.7 \
     --hash=sha256:00cf35c73405f9abff228297f9da010e36436fed9c157f05f7d3973ab48a7465 \
     --hash=sha256:023287ba3842b3040d98d8f5337e030a91ebfed95123ea48f46fbc862557afbc \
@@ -3480,11 +4043,22 @@ supervisor==4.3.0 \
 sympy==1.14.0 \
     --hash=sha256:d3d3fe8df1e5a0b42f0e7bdf50541697dbe7d23746e894990c030e2b05e72517 \
     --hash=sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5
-    # via torch
+    # via
+    #   einx
+    #   torch
+tables==3.11.1 \
+    --hash=sha256:1e78fe190fdeb4afe430b79651bae2a4f341904eb85aa8dbafe5f1caee1c7f67 \
+    --hash=sha256:56bf6fb9132ead989b7e76695d7613d6d08f071a8019038d6565ba90c66b9f3e \
+    --hash=sha256:78abcf413091bc7c1e4e8c10fbbb438d1ac0b5a87436c5b972c3e8253871b6fb \
+    --hash=sha256:7fa6cb03f6fe55ae4f85e89ec5450e5c40cc4c52d8c3b60eb157a445c2219e89 \
+    --hash=sha256:eb30684c42a77bbecdef2b9c763c4372b0ddc9cc5bd8b2a2055f2042eee67217 \
+    --hash=sha256:f0367d2e3df0f10ea63ccf4279f3fe58e32ec481767320301a483e2b3cd83efc
+    # via fuse-med-ml
 tabulate==0.10.0 \
     --hash=sha256:e2cfde8f79420f6deeffdeda9aaec3b6bc5abce947655d17ac662b126e48a60d \
     --hash=sha256:f0b0622e567335c8fabaaa659f1b33bcb6ddfe2e496071b743aa113f8774f2d3
     # via
+    #   biomed-multi-alignment
     #   flashinfer-python
     #   humming-kernels
 tacoreader==2.4.21 \
@@ -3518,7 +4092,9 @@ tblib==3.2.2 \
     # via tiledb-cloud
 tensorboard==2.21.0 \
     --hash=sha256:7279316dcb6bd5bc391d623dea841531299cde1887310e8133bc34a996d32255
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   terratorch
 tensorboard-data-server==0.7.2 \
     --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
     --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
@@ -3528,10 +4104,23 @@ tensorboardx==2.6.5 \
     --hash=sha256:c10b891d00af306537cb8b58a039b2ba41571f0da06f433a41c4ca8d6abe1373 \
     --hash=sha256:ca176db3997ee8c07d2eb77381225956a3fd1c10c91beafab1f17069adc47017
     # via bmfm-targets
+tensorflow==2.21.0 \
+    --hash=sha256:27ba0682572b1e50a0db1ee74cfb787eafcfdb1b751bbbf401fed62fe32a92e0 \
+    --hash=sha256:56ecd7d47429acbe1df2694d50b75bf9fc3995ac92cb367cd9af6c4780ead712 \
+    --hash=sha256:76cccbe0a95d9392dee1ae501ae0656b6c73c1cac29a7f8f32d570e0670863f7 \
+    --hash=sha256:a10abdfb8b1189210c251021a3f153b7ccc52a8e6521351f3dc3331e8ba593e0 \
+    --hash=sha256:a145ed46c58192b7c3f9916d070caf4f6afc6dc7e5511f83dd97677f4c4947f4 \
+    --hash=sha256:b07d15737406533898e36c7ef7944b1be18e9028dc521b9229952c537bbc5552 \
+    --hash=sha256:b3b95643c4e70eb925839938fb35cbe142f317ec84af6844ee61513713bb13c0 \
+    --hash=sha256:e9d8da8dcab9650efb45f032ba70af2f016f907e6e0c6bda29dd101bba945406
+    # via biomed-multi-alignment
 termcolor==3.3.0 \
     --hash=sha256:348871ca648ec6a9a983a13ab626c0acce02f515b9e1983332b17af7979521c5 \
     --hash=sha256:cf642efadaf0a8ebbbf4bc7a31cec2f9b5f21a9f726f4ccbb08192c9c26f43a5
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   tensorflow
+    #   terratorch
 terrakit==0.2.0 \
     --hash=sha256:683587a1f630ccbab5e345fdb2c8c0ee393aa450f0523b30ab1004aba1ca26a7 \
     --hash=sha256:e72951ceb6f4745554c47a633373de702caafde13690c440fbf8a16301b3508d
@@ -3545,7 +4134,9 @@ terratorch==1.2.10 \
 threadpoolctl==3.6.0 \
     --hash=sha256:43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb \
     --hash=sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e
-    # via scikit-learn
+    # via
+    #   blosc2
+    #   scikit-learn
 tifffile==2026.7.31 \
     --hash=sha256:79b1f4b1aba3ef3e6b6f1691a32abb62f5d7383faa52a12771c695232ba40bee \
     --hash=sha256:81adfa08012be1c478f99b83cda2f529eef8620cfbdf94fc41eef6f1d7b47dc5
@@ -3654,6 +4245,7 @@ tokenizers==0.22.2 \
     --hash=sha256:c9ea31edff2968b44a88f97d784c2f16dc0729b8b143ed004699ebca91f05c48 \
     --hash=sha256:df6c4265b289083bf710dff49bc51ef252f9d5be33a45ee2bed151114a56207b
     # via
+    #   fuse-med-ml
     #   transformers
     #   vllm
 tokenspeed-mla==0.1.8 ; sys_platform == 'linux' \
@@ -3711,12 +4303,14 @@ torch==2.11.0 \
     --hash=sha256:fbf39280699d1b869f55eac536deceaa1b60bd6788ba74f399cc67e60a5fab10
     # via
     #   accelerate
+    #   biomed-multi-alignment
     #   bmfm-targets
     #   captum
     #   cellxgene-census
     #   compressed-tensors
     #   flashinfer-python
     #   focal-loss-torch
+    #   fuse-med-ml
     #   humming-kernels
     #   kornia
     #   lightly
@@ -3731,11 +4325,14 @@ torch==2.11.0 \
     #   timm
     #   tokenspeed-mla
     #   torch-c-dlpack-ext
+    #   torch-einops-utils
     #   torchdata
     #   torchgeo
     #   torchmetrics
     #   torchvision
+    #   vit-pytorch
     #   vllm
+    #   x-transformers
     #   xgrammar
 torch-c-dlpack-ext==0.1.5 \
     --hash=sha256:30e3eab616dbc81dfdb7492aca557be551a9163ba9b585f97394a42b336b113a \
@@ -3750,6 +4347,10 @@ torch-c-dlpack-ext==0.1.5 \
     # via
     #   quack-kernels
     #   tilelang
+torch-einops-utils==0.1.12 \
+    --hash=sha256:9cbfe7e365d985c629a22830eea2541dcd990230a3e49a1916038938386b0bbe \
+    --hash=sha256:ab2b46a235a5ce6af0b29bff93ee83aecf4cacdb31cadc05de74eaf369708cd6
+    # via x-transformers
 torchaudio==2.11.0 \
     --hash=sha256:13cff988697ccbad539987599f9dc672f40c417bed67570b365e4e5002bbd096 \
     --hash=sha256:1c1101c1243ef0e4063ec63298977e2d3655c15cf88d9eb0a1bd4fe2db9f47ea \
@@ -3808,13 +4409,29 @@ torchvision==0.26.0 \
     --hash=sha256:d61a5abb6b42a0c0c311996c2ac4b83a94418a97182c83b055a2a4ae985e05aa \
     --hash=sha256:ebc043cc5a4f0bf22e7680806dbba37ffb19e70f6953bbb44ed1a90aeb5c9bea
     # via
+    #   fuse-med-ml
     #   lightly
     #   litdata
     #   segmentation-models-pytorch
     #   terratorch
     #   timm
     #   torchgeo
+    #   vit-pytorch
     #   vllm
+tornado==6.5.7 \
+    --hash=sha256:148b2eb15c2c765a50796172c1e499649b35f30d2e3c3d3e15913cfa56bfb163 \
+    --hash=sha256:66c513a76cda70d53907bc27cf1447557699c2e95aa48ba27a442ff61c3ddfc2 \
+    --hash=sha256:7778b30bef919231265e91c69963ce0f49a1e9c07ac900bbe75b19ce2575ba92 \
+    --hash=sha256:8a46347a18f23fb92b396beebe0fb78f61dda0cc302445202c16203d8a18848b \
+    --hash=sha256:8d759e71906ee783f8867b93bf26a265743da4c1e2f4a018464c1ba019862972 \
+    --hash=sha256:9da38de27f1da3b78a966f0dae12b5a1ea9afe72ca805d84ff06508272ddf100 \
+    --hash=sha256:de942f843533a039ef9fa3d9c88c7cd8a7c94553fb5ad0154270989b3d99a2c4 \
+    --hash=sha256:e726f0c75da7726eec023aa62751ff8878bd2737e34fbdd33b1ae5897d2200f5 \
+    --hash=sha256:f8de3bf12d3efdd0cbe7c8887868198f8a91415e3f29fcf258d9b8eb7b1d9ae4 \
+    --hash=sha256:ff934fce95643af5f11efdae618eaa73d469dc588641e5c8d19295a0c65c4796
+    # via
+    #   ipykernel
+    #   jupyter-client
 tqdm==4.70.0 \
     --hash=sha256:55b0b0dbd97462d06ebee91e4dac24ed4d4702be82b24f07e6c1d27e08cea220 \
     --hash=sha256:7f585706bfddbdebf89daac705b2dfcc16890130727d3197ca62c732b4310953
@@ -3822,6 +4439,7 @@ tqdm==4.70.0 \
     #   captum
     #   cdsapi
     #   flashinfer-python
+    #   fuse-med-ml
     #   huggingface-hub
     #   humming-kernels
     #   lightly
@@ -3841,12 +4459,23 @@ tqdm==4.70.0 \
     #   transformers
     #   umap-learn
     #   vllm
+traitlets==5.16.1 \
+    --hash=sha256:ed900c2b631aa3a112811139fa97b8d2c3bad5e989656bba4b7e52c7852c18c1 \
+    --hash=sha256:f775618166caa0396c8e337099240f2bd3e5e917d203b2e6fbe21a58d3cb1f6b
+    # via
+    #   ipykernel
+    #   ipython
+    #   jupyter-client
+    #   jupyter-core
+    #   matplotlib-inline
 transformers==5.14.1 \
     --hash=sha256:60d196c27781eacf8637e2b533f517582907ad6f9ae142046d6b69431a5b2173 \
     --hash=sha256:9db974c4079ede2d1a3ea7ca5a240df33f2cc26fc2b36ba64c5f2a4f43b6e725
     # via
+    #   biomed-multi-alignment
     #   bmfm-targets
     #   compressed-tensors
+    #   fuse-med-ml
     #   peft
     #   vllm
     #   xgrammar
@@ -3891,14 +4520,17 @@ typing-extensions==4.16.0 \
     #   cuda-tile
     #   ecmwf-datastores-client
     #   fastapi
+    #   formulaic
     #   grpcio
     #   httpx2
     #   huggingface-hub
+    #   jupyter-client
     #   lightning
     #   lightning-utilities
     #   mcp
     #   mcp-types
     #   mistral-common
+    #   nibabel
     #   nvidia-cutlass-dsl-libs-base
     #   nvidia-cutlass-dsl-libs-core
     #   nvidia-cutlass-dsl-libs-cu12
@@ -3910,6 +4542,7 @@ typing-extensions==4.16.0 \
     #   opentelemetry-exporter-otlp-proto-http
     #   opentelemetry-sdk
     #   opentelemetry-semantic-conventions
+    #   optree
     #   pandera
     #   pydantic
     #   pydantic-core
@@ -3923,6 +4556,7 @@ typing-extensions==4.16.0 \
     #   sentinelhub
     #   somacore
     #   starlette
+    #   tensorflow
     #   tiledb-cloud
     #   tiledb-vector-search
     #   tiledbsoma
@@ -3997,12 +4631,17 @@ uvloop==0.22.1 ; platform_python_implementation != 'PyPy' and sys_platform != 'c
     --hash=sha256:e047cc068570bac9866237739607d1313b9253c3051ad84738cbb095be0537b2 \
     --hash=sha256:fe94b4564e865d968414598eea1a6de60adba0c040ba4ed05ac1300de402cd42
     # via uvicorn
+vit-pytorch==1.24.2 \
+    --hash=sha256:049b78b63981f67af4bb773e67c094b47d3a61c0b500959f66b6c223909cbfa2 \
+    --hash=sha256:77e7b9dbd034821b31064aeaf53f7bcd22c32a1eb70e1915d9681978a5af2d93
+    # via fuse-med-ml
 vllm==0.26.0 \
     --hash=sha256:23e9fa19d7e20ce7dcc1c074d41503e2116d23f19e688f5d5ea91b741f958502 \
     --hash=sha256:52a4c3e55c2c80cc8793e52ccc244457ceade25b0ad7caa1c15e5002a95a1b2c \
     --hash=sha256:adb1e4c9b46d0dfdb094121ae5aad670a42412dd813ed4e5db069ed6a15006de
     # via
     #   algorithm-nexus
+    #   biomed-multi-alignment
     #   bmfm-targets
     #   terratorch
 watchfiles==1.2.0 \
@@ -4049,6 +4688,10 @@ watchfiles==1.2.0 \
     # via
     #   uvicorn
     #   vllm
+wcwidth==0.8.2 \
+    --hash=sha256:91fbef97204b96a3d4d421609b80340b760cf33e26da123ff243d76b1fda8dda \
+    --hash=sha256:d63947694a0539a1d51e01eda7caf800c291020e6cdd7e28ad7b14dd33ad4f85
+    # via prompt-toolkit
 websockets==17.0.1 \
     --hash=sha256:02ed63bf26dda9fa27df730a41f6664586c4ee05972c8fb667ce1725b3fd13d3 \
     --hash=sha256:07abc3bd196a48af476a82fd47f3f79a6a3f70937a9f930cef703cfa0c9d83b6 \
@@ -4097,6 +4740,13 @@ werkzeug==3.1.8 \
     --hash=sha256:63a77fb8892bf28ebc3178683445222aa500e48ebad5ec77b0ad80f8726b1f50 \
     --hash=sha256:9bad61a4268dac112f1c5cd4630a56ede601b6ed420300677a869083d70a4c44
     # via tensorboard
+wget==3.2 \
+    --hash=sha256:35e630eca2aa50ce998b9b1a127bb26b30dfee573702782aa982f875e3f16061
+    # via fuse-med-ml
+wheel==0.47.0 \
+    --hash=sha256:212281cab4dff978f6cedd499cd893e1f620791ca6ff7107cf270781e587eced \
+    --hash=sha256:cc72bd1009ba0cf63922e28f94d9d83b920aa2bb28f798a31d0691b02fa3c9b3
+    # via astunparse
 win32-setctime==1.2.0 ; sys_platform == 'win32' \
     --hash=sha256:95d644c4e708aba81dc3704a116d8cbc974d70b3bdb8be1d150e36be6e9d1390 \
     --hash=sha256:ae1fdf948f5640aae05c511ade119313fb6a30d7eabe25fef9764dca5873c4c0
@@ -4140,6 +4790,12 @@ wrapt==2.3.0 \
     # via
     #   aiobotocore
     #   deprecated
+    #   formulaic
+    #   tensorflow
+x-transformers==2.25.4 \
+    --hash=sha256:550872f0fbe089d83f45b1eb9b9d5304102369c77ce04a07559d88dd9b1b2832 \
+    --hash=sha256:d4e71a9938369851d88e22fa462d5c3545a0dee9f606fa330017e0836c3d0eb7
+    # via fuse-med-ml
 xarray==2026.7.0 \
     --hash=sha256:361b495928fdbf5b58d0969bb6775339019da5e93ca74d61ddf4eb5edd6ce604 \
     --hash=sha256:bf9dd130b93806dc78e90c1b7ac24851b31557b888674c53622235691cf21824
diff --git a/requirements-ecosystem.txt b/requirements-ecosystem.txt
index 83c1a5b..896ca44 100644
--- a/requirements-ecosystem.txt
+++ b/requirements-ecosystem.txt
@@ -1,7 +1,10 @@
 absl-py==2.5.0 \
     --hash=sha256:0c996f25c0490700fadabe6351630f6111534fa0ae252cc6d2014ea3b141135f \
     --hash=sha256:0f17b89f2a4eaaedc4f28c622998aa690564b3012a396a4ffad0821007fe03ba
-    # via tensorboard
+    # via
+    #   keras
+    #   tensorboard
+    #   tensorflow
 accelerate==1.14.0 \
     --hash=sha256:41b9c4377a54e0b460a959b0defa1b736e4ca0a2373252d9a539964c2afe3c8d \
     --hash=sha256:e94390c2863b873be18f623f9df48a0d8fe5eff13ea7f1a00092b0a7904888c6
@@ -140,6 +143,10 @@ asttokens==3.0.2 \
     --hash=sha256:3ecdbd8f2cc195f53ccada3a613538bb5f9ef6f6869129f13e03c30a677b8fe2 \
     --hash=sha256:9da13157f5b28becde0bd374fc677dcd3c290614264eff096f167c469cd9f933
     # via stack-data
+astunparse==1.6.3 \
+    --hash=sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872 \
+    --hash=sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8
+    # via tensorflow
 attrs==26.1.0 \
     --hash=sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309 \
     --hash=sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32
@@ -153,14 +160,87 @@ attrs==26.1.0 \
     #   somacore
     #   tiledb-cloud
     #   tiledbsoma
+autograd==1.9.1 \
+    --hash=sha256:7818c5c69ddf9efb7da74097bd741a4c7920133f41966f68537223a15ef798bc \
+    --hash=sha256:b788bae3fa010cbffb4cfb7b8ba2a3f0daa6072a8506da6164c779fe9cf3e05a
+    # via
+    #   autograd-gamma
+    #   lifelines
+autograd-gamma==0.5.0 \
+    --hash=sha256:f27abb7b8bb9cffc8badcbf59f3fe44a9db39e124ecacf1992b6d952934ac9c4
+    # via lifelines
+bcrypt==5.0.0 \
+    --hash=sha256:0c418ca99fd47e9c59a301744d63328f17798b5947b0f791e9af3c1c499c2d0a \
+    --hash=sha256:0c8e093ea2532601a6f686edbc2c6b2ec24131ff5c52f7610dd64fa4553b5464 \
+    --hash=sha256:137c5156524328a24b9fac1cb5db0ba618bc97d11970b39184c1d87dc4bf1746 \
+    --hash=sha256:200af71bc25f22006f4069060c88ed36f8aa4ff7f53e67ff04d2ab3f1e79a5b2 \
+    --hash=sha256:212139484ab3207b1f0c00633d3be92fef3c5f0af17cad155679d03ff2ee1e41 \
+    --hash=sha256:2b732e7d388fa22d48920baa267ba5d97cca38070b69c0e2d37087b381c681fd \
+    --hash=sha256:35a77ec55b541e5e583eb3436ffbbf53b0ffa1fa16ca6782279daf95d146dcd9 \
+    --hash=sha256:38cac74101777a6a7d3b3e3cfefa57089b5ada650dce2baf0cbdd9d65db22a9e \
+    --hash=sha256:3abeb543874b2c0524ff40c57a4e14e5d3a66ff33fb423529c88f180fd756538 \
+    --hash=sha256:3ca8a166b1140436e058298a34d88032ab62f15aae1c598580333dc21d27ef10 \
+    --hash=sha256:3cf67a804fc66fc217e6914a5635000259fbbbb12e78a99488e4d5ba445a71eb \
+    --hash=sha256:4bfd2a34de661f34d0bda43c3e4e79df586e4716ef401fe31ea39d69d581ef23 \
+    --hash=sha256:560ddb6ec730386e7b3b26b8b4c88197aaed924430e7b74666a586ac997249ef \
+    --hash=sha256:5b1589f4839a0899c146e8892efe320c0fa096568abd9b95593efac50a87cb75 \
+    --hash=sha256:5feebf85a9cefda32966d8171f5db7e3ba964b77fdfe31919622256f80f9cf42 \
+    --hash=sha256:611f0a17aa4a25a69362dcc299fda5c8a3d4f160e2abb3831041feb77393a14a \
+    --hash=sha256:61afc381250c3182d9078551e3ac3a41da14154fbff647ddf52a769f588c4172 \
+    --hash=sha256:64d7ce196203e468c457c37ec22390f1a61c85c6f0b8160fd752940ccfb3a683 \
+    --hash=sha256:64ee8434b0da054d830fa8e89e1c8bf30061d539044a39524ff7dec90481e5c2 \
+    --hash=sha256:741449132f64b3524e95cd30e5cd3343006ce146088f074f31ab26b94e6c75ba \
+    --hash=sha256:7aeef54b60ceddb6f30ee3db090351ecf0d40ec6e2abf41430997407a46d2254 \
+    --hash=sha256:801cad5ccb6b87d1b430f183269b94c24f248dddbbc5c1f78b6ed231743e001c \
+    --hash=sha256:83e787d7a84dbbfba6f250dd7a5efd689e935f03dd83b0f919d39349e1f23f83 \
+    --hash=sha256:89042e61b5e808b67daf24a434d89bab164d4de1746b37a8d173b6b14f3db9ff \
+    --hash=sha256:9d52ed507c2488eddd6a95bccee4e808d3234fa78dd370e24bac65a21212b861 \
+    --hash=sha256:9fffdb387abe6aa775af36ef16f55e318dcda4194ddbf82007a6f21da29de8f5 \
+    --hash=sha256:a71f70ee269671460b37a449f5ff26982a6f2ba493b3eabdd687b4bf35f875ac \
+    --hash=sha256:baade0a5657654c2984468efb7d6c110db87ea63ef5a4b54732e7e337253e44f \
+    --hash=sha256:c2388ca94ffee269b6038d48747f4ce8df0ffbea43f31abfa18ac72f0218effb \
+    --hash=sha256:c58b56cdfb03202b3bcc9fd8daee8e8e9b6d7e3163aa97c631dfcfcc24d36c86 \
+    --hash=sha256:cde08734f12c6a4e28dc6755cd11d3bdfea608d93d958fffbe95a7026ebe4980 \
+    --hash=sha256:d79e5c65dcc9af213594d6f7f1fa2c98ad3fc10431e7aa53c176b441943efbdd \
+    --hash=sha256:d8d65b564ec849643d9f7ea05c6d9f0cd7ca23bdd4ac0c2dbef1104ab504543d \
+    --hash=sha256:db99dca3b1fdc3db87d7c57eac0c82281242d1eabf19dcb8a6b10eb29a2e72d1 \
+    --hash=sha256:ddb4e1500f6efdd402218ffe34d040a1196c072e07929b9820f363a1fd1f4191 \
+    --hash=sha256:e3cf5b2560c7b5a142286f69bde914494b6d8f901aaa71e453078388a50881c4 \
+    --hash=sha256:ed2e1365e31fc73f1825fa830f1c8f8917ca1b3ca6185773b349c20fd606cec2 \
+    --hash=sha256:edfcdcedd0d0f05850c52ba3127b1fce70b9f89e0fe5ff16517df7e81fa3cbb8 \
+    --hash=sha256:f0ce778135f60799d89c9693b9b398819d15f1921ba15fe719acb3178215a7db \
+    --hash=sha256:f2347d3534e76bf50bca5500989d6c1d05ed64b440408057a37673282c654927 \
+    --hash=sha256:f3c08197f3039bec79cee59a606d62b96b16669cff3949f21e74796b6e3cd2be \
+    --hash=sha256:f632fd56fc4e61564f78b46a2269153122db34988e78b6be8b32d28507b7eaeb \
+    --hash=sha256:f6984a24db30548fd39a44360532898c33528b74aedf81c26cf29c51ee47057e \
+    --hash=sha256:f748f7c2d6fd375cc93d3fba7ef4a9e3a092421b8dbf34d8d4dc06be9492dfdd \
+    --hash=sha256:f8429e1c410b4073944f03bd778a9e066e7fad723564a52ff91841d278dfc822 \
+    --hash=sha256:fc746432b951e92b58317af8e0ca746efe93e66555f1b40888865ef5bf56446b
+    # via paramiko
 beautifulsoup4==4.15.0 \
     --hash=sha256:288e3ca7d54b06f2ac191970bc275c1939cb46d450b255bf6718b04aa37ab4f7 \
     --hash=sha256:d6f88de62e1d4e38ecb1077eb9724cd0eff29d2a08ca16a401e9b9e93f117cf9
     # via gdown
+biomed-multi-alignment @ git+https://github.com/BiomedSciAI/biomed-multi-alignment@8cc56e9494b489ca86a63b76fa4cd2921f8af7f7
+    # via algorithm-nexus
 blinker==1.9.0 \
     --hash=sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf \
     --hash=sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc
     # via flask
+blosc2==4.10.1 \
+    --hash=sha256:77f2191c0be24c82d88cdcf7f45634602c996bd082ef9ff73a4d2a20b1340391 \
+    --hash=sha256:7b4b1dcc4da3198c4747bb88a62fc1664e3dc8fb727d505c85e283302ce7b8d4 \
+    --hash=sha256:7c66bd1f69683a63d4b9e5f8285ff951e1a0057bac5d2f68dee1564abaa8c277 \
+    --hash=sha256:acae1bc45fa0ba927270822b0f05d2f135309eebdcb1ea89383198996bc7702b \
+    --hash=sha256:b81e31335127eca1a6bfad235e45723c1b25fe0e8a99d5f830ea791d3da17839 \
+    --hash=sha256:b86f45f236ef2a812778ae2af7b530477db36693df4e464c29a75b6246b4dbaa \
+    --hash=sha256:c1196f12ccc19181743b7f66edceccf1981cf1b885c78a3a4f27b1a41e6541d4 \
+    --hash=sha256:d412cdf216e8fe4cffbe76a926c98c37a2419b14ba5c4be7f771f73e7d7b1840 \
+    --hash=sha256:d8dbaa028160992b03e3668578ef9668e09cdd11c2534646831a6a36d321cc8a \
+    --hash=sha256:e6649b94c28eb90a4c7dc5703cb67a5eb5121e891139c5ded2b75a172291d011 \
+    --hash=sha256:ee7f4b39a045fc77ec7d67381a95399d30885c208e71278c38f59b5ae29e8028 \
+    --hash=sha256:f37bb784c56b4fe11a0e23a011c609d08ebab0fe19fb2e75cea5e9ab13f9cbf2
+    # via tables
 bmfm-targets @ git+https://github.com/BiomedSciAI/biomed-multi-omic.git@8b5694a922be7ccb1d3ee5c280c4dcef2eb95df9
     # via algorithm-nexus
 boto3==1.43.56 \
@@ -180,6 +260,51 @@ branca==0.8.2 \
     --hash=sha256:2ebaef3983e3312733c1ae2b793b0a8ba3e1c4edeb7598e10328505280cf2f7c \
     --hash=sha256:e5040f4c286e973658c27de9225c1a5a7356dd0702a7c8d84c0f0dfbde388fe7
     # via folium
+cachebox==5.2.3 \
+    --hash=sha256:09c0340e9daa7b4530801e5a570cb0c1a1ad941a85d245d360020d3986d0e787 \
+    --hash=sha256:0a17aeb4e5b1c6ef1c3db8fc5186f9986e215ba5ea5a5d08baa45bcf55f261b2 \
+    --hash=sha256:10bedf96db8f9766cc956f9adcc623e604264e5d6fa2e255432f8c2ed7519143 \
+    --hash=sha256:26ae0b68979204d360327f4c0725cfdc95cfc34ab73ab1a8f528e3bd2f6d023c \
+    --hash=sha256:2a1e7d3cb8a5e7e68996a8619e3ef8771a124d14568c251f9e586eba88d759c1 \
+    --hash=sha256:2f1e086ab5ffd082a68bb63699d517655a59b06414927bfc84e01df91b81e34d \
+    --hash=sha256:405f9cc8492fc9d953b5a6b9e2b661e99583755c6639ab8d09a287fdf336503c \
+    --hash=sha256:40ac878af00d5969862c1f6bc076de1e34ca248662fce6aecca1761f52e33e32 \
+    --hash=sha256:410b67baa99d433644199b11289627f7ebba4ee5786f95ca9858f238afcee157 \
+    --hash=sha256:41e99c1240106d39b63ce7868a6cd8c9da9243fef08848b85d428164e0769fd2 \
+    --hash=sha256:432ca62b99f7eafc21af669d76c88c1b7377db179b89fb6fca3ea93b8f9fff19 \
+    --hash=sha256:55003089d21c2f5515089c307be063b45558e884a4a1cc9593944374c89975c4 \
+    --hash=sha256:5e48a405f699fb001b8af120a6e0b4a981277f84eb5dd66a1faa21e4b6fe9485 \
+    --hash=sha256:5fee33549877c03c2494ec5359a57a7667f872fe8e296a7f39d3dfe08dd3914c \
+    --hash=sha256:64057caa6b741320655cd3c5997fe642dae5dbff571eb530e6f53e58272bb43b \
+    --hash=sha256:649d18399f13735bb82daa33800196f815529c49e967767c40ca221723e68afa \
+    --hash=sha256:67548a05cd41fcc4f7af80a2f97f742fef3d436537ac2e1a1dce0fcba5d41190 \
+    --hash=sha256:6a94d0da8133b3a0707ae11c9ea321f8fc37e3b5a14517019a05d632218b0f56 \
+    --hash=sha256:82e7002dd343afeeba2fcf0e483131b342a27ec3bc34b2214dc617691bda40d6 \
+    --hash=sha256:8342ff350ce86f062492752d612e9f056ac5dc56375713d75c3bf6e83b4d18db \
+    --hash=sha256:85ccd827193b3e3e887a88a16b88ef7ed174e7e65be515b5253322aa75e665c3 \
+    --hash=sha256:8cbfc007ea78af61d75d7d26e5854df53dc5da6877d074afd4b4696c074f4ee7 \
+    --hash=sha256:94aae393ec1d9b26565d346445bb6afa3963d2a0d3eb5e4188d0e510fab871a0 \
+    --hash=sha256:9527c5c70f8735f2d696331d8bcf77254f03b4dc8542046807823bd36ed4e8ba \
+    --hash=sha256:a189a780c3ccd7b9d157074ba6bf3e191e522b39abbdb590075111851f02d50d \
+    --hash=sha256:a4b7559fa4994c4032dd07466c2041d57e055feb814762e1f73f4e8beef188d0 \
+    --hash=sha256:a8b0b575066fc09f6fae0d4bd30d6ff56584a6870cbe7d202916c5e0d725cfd4 \
+    --hash=sha256:adcedfcfcb933b21e7fdcfe560c79887bc8287abceab0586aa3730417dd0277d \
+    --hash=sha256:b1f68246685aa739bbbd2734befb1465363a1e1042407c154feadb065f17a099 \
+    --hash=sha256:b5ff26bfd8f7e95b3becf6d5f65c25edaca50fa68078868648b70d79bcccc260 \
+    --hash=sha256:c48c10e498d573511aafbd545570e7f43b40a7428dc282183bf5adc334d9e1a8 \
+    --hash=sha256:c7f0c72c51a3a9e7049ea6ff2a43cd3877ab7fee966eb65771a59621563b75e3 \
+    --hash=sha256:ccbdc54a6c4b5758408c1083bdfa217bd382894a8331c7d0a54b84ba0cf51e5b \
+    --hash=sha256:cfd69114141ab362acaa2099e425a1b965cf7b021a539a4e953143d593930b74 \
+    --hash=sha256:dcc5edb6ecf2b516e90b773d232360c5e4ed8fdcda038b19441da2ed9cf208ab \
+    --hash=sha256:df5135a168f143d186b1cc3be0ca16b66446897ab5cedc03bd80bcc926fcd403 \
+    --hash=sha256:e51d9c59006b53447f806145406eb37a7fc3c25553d4fd24c3887f3b268d214e \
+    --hash=sha256:f22732d0d69bb84ad2dca7480bffdfd0430c647152d488936e152ecbbfee52fb \
+    --hash=sha256:f3162758792626685ec34950eedd565d015b115d0ff0d751d2716031fc32d51b \
+    --hash=sha256:f3d628b816e28a6e7661d460e02dd5b421247cc2cd275814f80ea79621245fc4 \
+    --hash=sha256:f57afada3d9327adf87f3b5cf0094348c6fd49354ab2e9bd20b044648eb094ae \
+    --hash=sha256:f81474dc19d3865fa5e57263f834bc6bbc00e471a594fb9d934ed552732c02fd \
+    --hash=sha256:fa325306084aa2dc0b21e07723d7700f4d43dece3732c7fdaf7a269dc5e35aa7
+    # via deepdiff
 cachetools==7.1.7 \
     --hash=sha256:a3e2a00b14d8f8a6b70c1dae7b4685e7ad3bc965c5b42124a2d6ce895da6cf50 \
     --hash=sha256:ef98ef375ad188819ef2f9b3645e3987f4b8c5b7550e436ad998c2de78296df0
@@ -242,6 +367,7 @@ cffi==2.1.1 ; implementation_name == 'pypy' or platform_python_implementation !=
     --hash=sha256:fcd22650c908d7b7da162bbfaab594a1227a15d1643a98c68b122ac642fa2264
     # via
     #   cryptography
+    #   pynacl
     #   pyzmq
 cftime==1.6.5 \
     --hash=sha256:18ab754805233cdd889614b2b3b86a642f6d51a57a1ec327c48053f3414f87d8 \
@@ -290,9 +416,16 @@ charset-normalizer==3.4.9 \
     --hash=sha256:e4fd89cc178bced6ad29cb3e6dd4aa63fa5017c3524dbd0b25998fb64a87cc8b \
     --hash=sha256:fe2c7201c642b7c308f1675355ad7ff7b66acfe3541625efe5a3ad38f29d6115
     # via requests
+choix==0.4.1 \
+    --hash=sha256:15fe145ffc194dc6b4ba5a44ef24667fa0107578fb5b36723ab0b5e87eeae29f \
+    --hash=sha256:7c85d13845400932508c45a6a6a3e7a44f637969ffd506e1c7f5db07de1560b4
+    # via fuse-med-ml
 clearml==1.18.0 \
     --hash=sha256:fe53ffcfdb0799150ad5ae1ca95bdbd568e570cbde2e35a65474e36606a899d0
-    # via bmfm-targets
+    # via
+    #   biomed-multi-alignment
+    #   bmfm-targets
+    #   fuse-med-ml
 click==8.4.2 \
     --hash=sha256:9a6cea6e60b17ebe0a44c5cc636d94f09bd66142c1cd7d8b4cd731c4917a15f6 \
     --hash=sha256:e6f9f66136c816745b9d65817da91d61d957fb16e02e4dcd0552553c5a197b76
@@ -300,6 +433,7 @@ click==8.4.2 \
     #   cligj
     #   dask
     #   flask
+    #   fuse-med-ml
     #   huggingface-hub
     #   mercantile
     #   mlflow-skinny
@@ -324,6 +458,8 @@ colorama==0.4.6 ; sys_platform == 'win32' \
     # via
     #   click
     #   ipython
+    #   loguru
+    #   pytest
     #   tqdm
     #   typer
 comm==0.2.3 \
@@ -403,6 +539,7 @@ cryptography==49.0.0 \
     # via
     #   google-auth
     #   mlflow
+    #   paramiko
 cuda-bindings==13.3.1 ; sys_platform == 'linux' \
     --hash=sha256:18c8c167c8907b8f02531ca810534315c458dabef31f7965095619bf647b9202 \
     --hash=sha256:2732904099e0a4d4db774a5fc6d91ee95fae065b4d2ecabb4968c5fe2406c9d7 \
@@ -449,6 +586,10 @@ debugpy==1.8.21 \
     --hash=sha256:c193d474f0a211191f2b4449d2d06157c689013035bd952f3b617e0ef422b176 \
     --hash=sha256:ecbd158386c31ffe71d46f72d44d56e66331ab9b16cad649156d514368f23ab2
     # via ipykernel
+deepdiff==9.1.0 \
+    --hash=sha256:07e9e366fab4297755153c4eab795ad4ef3cbd0d51660e847f5751c6bd727687 \
+    --hash=sha256:80c0460e1993b04f6f0ca79abf25548b129fd218478c4ebb08f80560f5d10610
+    # via fuse-med-ml
 deprecated==1.3.1 \
     --hash=sha256:597bfef186b6f60181535a29fbe44865ce137a5079f295b479886c82729d5f3f \
     --hash=sha256:b1b50e0ff0c1fddaa5708a2c6b0a6588bb09b892825ab2b214ac9ea9d92a5223
@@ -496,7 +637,14 @@ einops==0.8.2 \
     # via
     #   bmfm-targets
     #   terratorch
+    #   torch-einops-utils
     #   torchgeo
+    #   vit-pytorch
+    #   x-transformers
+einx==0.4.3 \
+    --hash=sha256:47ce54a0144f6dffcfacdd8fe2cc9e2e5e6485dda2471330ab75ee747dd22f39 \
+    --hash=sha256:be7d81ea1908b9f00e4a467840998fc483c33aa32aaaaa3ada6c8386f693edf9
+    # via x-transformers
 executing==2.2.1 \
     --hash=sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4 \
     --hash=sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017
@@ -533,6 +681,9 @@ flask-cors==6.0.5 \
     --hash=sha256:30c5031552cd59f620ac0c8211dac45b345d3b2df310e7721879e4f46ef9c601 \
     --hash=sha256:68fcf75693e961f3af26683b23c4b9a8fb6b64de17d20d0c37b95e8de7ab2ed8
     # via mlflow
+flatbuffers==25.12.19 \
+    --hash=sha256:7634f50c427838bb021c2d66a3d1168e9d199b0607e6329399f04846d42e20b4
+    # via tensorflow
 focal-loss-torch @ git+https://github.com/mathiaszinnen/focal_loss_torch.git@69fd65795f2688c2c302029f383f1b58978c1123
     # via bmfm-targets
 folium==0.20.0 \
@@ -559,6 +710,14 @@ fonttools==4.63.0 \
     --hash=sha256:ee08ebfa58f6e1aeff5697ab9582105bb620008c1caafb681e4c557e7483027b \
     --hash=sha256:ef3048ef05dbb552b89817713d9cac912e00d0fde4a3105c00d29e52e10c89af
     # via matplotlib
+formulaic==1.2.2 \
+    --hash=sha256:0f84ff49e3fc9dc0e68ab08a0a9427874021aa6c558e66b44dc634a35739b09b \
+    --hash=sha256:c99e8f11ff7d327eaecaf63855ca69b7fa0da100ad6c0041ef80912fbac667e6
+    # via lifelines
+frozendict==2.4.7 \
+    --hash=sha256:972af65924ea25cf5b4d9326d549e69a9a4918d8a76a9d3a7cd174d98b237550 \
+    --hash=sha256:e478fb2a1391a56c8a6e10cc97c4a9002b410ecd1ac28c18d780661762e271bd
+    # via einx
 frozenlist==1.8.0 \
     --hash=sha256:032efa2674356903cd0261c4317a561a6850f3ac864a63fc1583147fb05a79b0 \
     --hash=sha256:03ae967b4e297f58f8c774c7eabcce57fe3c2434817d4385c50661845a058121 \
@@ -628,6 +787,14 @@ furl==2.1.4 \
     --hash=sha256:877657501266c929269739fb5f5980534a41abd6bbabcb367c136d1d3b2a6015 \
     --hash=sha256:da34d0b34e53ffe2d2e6851a7085a05d96922b5b578620a37377ff1dbeeb11c8
     # via clearml
+fuse-med-ml==0.4.1 \
+    --hash=sha256:df7b8a67b34f96917e3d40308fa6d6a36f028d7b1c48934263524a1149f8fafd \
+    --hash=sha256:f7d1a0931868cd319627bfd201c8c0312f08901331c68f02afee1fbf5cd77398
+    # via biomed-multi-alignment
+gast==0.7.0 \
+    --hash=sha256:0bb14cd1b806722e91ddbab6fb86bba148c22b40e7ff11e248974e04c8adfdae \
+    --hash=sha256:99cbf1365633a74099f69c59bd650476b96baa5ef196fec88032b00b31ba36f7
+    # via tensorflow
 gdown==6.1.0 \
     --hash=sha256:361c6e04c6ca335df50b9d71f40bcfe9ab70fb26a1b0e890a427267781389553 \
     --hash=sha256:38a36a94275b8272f684db469bbd73b4d1f64cbbc1751bcb993a1b2be8f013c8
@@ -676,6 +843,10 @@ google-crc32c==1.8.0 \
     --hash=sha256:a428e25fb7691024de47fecfbff7ff957214da51eddded0da0ae0e0f03a2cf79 \
     --hash=sha256:cb5c869c2923d56cb0c8e6bcdd73c009c36ae39b652dbe46a05eb4ef0ad01454
     # via zarr
+google-pasta==0.2.0 \
+    --hash=sha256:b32482794a366b5366a32c92a9a9201b107821889935a02b3e51f6b432ea84ed \
+    --hash=sha256:c9f2c8dfc8f96d0d5808299920721be30c9eec37f2389f28904f454565c8a16e
+    # via tensorflow
 graphene==3.4.3 \
     --hash=sha256:2a3786948ce75fe7e078443d37f609cbe5bb36ad8d6b828740ad3b95ed1a0aaa \
     --hash=sha256:820db6289754c181007a150db1f7fff544b94142b556d12e3ebc777a7bf36c71
@@ -743,7 +914,9 @@ grpcio==1.83.0 \
     --hash=sha256:cb2906c61db4f9c64cc360054b5df70eeb81846228e9e56a4944bd415a63dadc \
     --hash=sha256:f1c3e5689d4b90987b1d72022bcfe866a9a3dc66197484cf856d96b6150e7f45 \
     --hash=sha256:f47d62808b4c0a97b78bff88a6d4ca283a2a492b9a04a87d814af95ca3b9c19c
-    # via tensorboard
+    # via
+    #   tensorboard
+    #   tensorflow
 gunicorn==26.0.0 ; sys_platform != 'win32' \
     --hash=sha256:40233d26a5f0d1872916188c276e21641155111c2853f0c2cd55260aec0d24fc \
     --hash=sha256:ca9346f85e3a4aeeb64d491045c16b9a35647abd37ea15efe53080eb8b090baf
@@ -754,28 +927,39 @@ h11==0.16.0 \
     # via
     #   httpcore
     #   uvicorn
-h5py==3.16.0 \
-    --hash=sha256:099f2525c9dcf28de366970a5fb34879aab20491589fa89ce2863a84218bb524 \
-    --hash=sha256:171038f23bccddfc23f344cadabdfc9917ff554db6a0d417180d2747fe4c75a7 \
-    --hash=sha256:18f2bbcd545e6991412253b98727374c356d67caa920e68dc79eab36bf5fedad \
-    --hash=sha256:2b2c02b0a160faed5fb33f1ba8a264a37ee240b22e049ecc827345d0d9043074 \
-    --hash=sha256:370a845f432c2c9619db8eed334d1e610c6015796122b0e57aa46312c22617d9 \
-    --hash=sha256:39c2838fb1e8d97bcf1755e60ad1f3dd76a7b2a475928dc321672752678b96db \
-    --hash=sha256:42108e93326c50c2810025aade9eac9d6827524cdccc7d4b75a546e5ab308edb \
-    --hash=sha256:42b012933a83e1a558c673176676a10ce2fd3759976a0fedee1e672d1e04fc9d \
-    --hash=sha256:656f00e4d903199a1d58df06b711cf3ca632b874b4207b7dbec86185b5c8c7d4 \
-    --hash=sha256:698dd69291272642ffda44a0ecd6cd3bda5faf9621452d255f57ce91487b9794 \
-    --hash=sha256:7e420b539fb6023a259a1b14d4c9f6df8cf50d7268f48e161169987a57b737ff \
-    --hash=sha256:9300ad32dea9dfc5171f94d5f6948e159ed93e4701280b0f508773b3f582f402 \
-    --hash=sha256:96b422019a1c8975c2d5dadcf61d4ba6f01c31f92bbde6e4649607885fe502d6 \
-    --hash=sha256:a0dbaad796840ccaa67a4c144a0d0c8080073c34c76d5a6941d6818678ef2738 \
-    --hash=sha256:c5313566f4643121a78503a473f0fb1e6dcc541d5115c44f05e037609c565c4d \
-    --hash=sha256:dfc21898ff025f1e8e67e194965a95a8d4754f452f83454538f98f8a3fcb207e \
-    --hash=sha256:ff24039e2573297787c3063df64b60aab0591980ac898329a08b0320e0cf2527
+h2==4.4.1 \
+    --hash=sha256:0e25f1462b23c9cb82d9eb02e28bc706dac2a68cb457c6a0d74d63c8a2a5d0e6 \
+    --hash=sha256:4e866ffb1a869ae14dd9b5e6beb5c24a13da0495ad72b65925ded182521c1516
+    # via httpx
+h5py==3.14.0 \
+    --hash=sha256:0cbd41f4e3761f150aa5b662df991868ca533872c95467216f2bec5fcad84882 \
+    --hash=sha256:2372116b2e0d5d3e5e705b7f663f7c8d96fa79a4052d250484ef91d24d6a08f4 \
+    --hash=sha256:554ef0ced3571366d4d383427c00c966c360e178b5fb5ee5bb31a435c424db0c \
+    --hash=sha256:6da62509b7e1d71a7d110478aa25d245dd32c8d9a1daee9d2a42dba8717b047a \
+    --hash=sha256:aa4b7bbce683379b7bf80aaba68e17e23396100336a8d500206520052be2f812 \
+    --hash=sha256:ae18e3de237a7a830adb76aaa68ad438d85fe6e19e0d99944a3ce46b772c69b3 \
+    --hash=sha256:bf4897d67e613ecf5bdfbdab39a1158a64df105827da70ea1d90243d796d367f \
+    --hash=sha256:d90e6445ab7c146d7f7981b11895d70bc1dd91278a4f9f9028bc0c95e4a53f13 \
+    --hash=sha256:e0045115d83272090b0717c555a31398c2c089b87d212ceba800d3dc5d952e23 \
+    --hash=sha256:e8cbaf6910fa3983c46172666b0b8da7b7bd90d764399ca983236f2400436eeb \
+    --hash=sha256:ef9603a501a04fcd0ba28dd8f0995303d26a77a980a1f9474b3417543d4c6174
     # via
     #   anndata
+    #   fuse-med-ml
+    #   hdf5plugin
+    #   keras
     #   scanpy
+    #   tensorflow
     #   terratorch
+hdf5plugin==7.0.0 \
+    --hash=sha256:0f3ba9f4e2a370340b45e7042d1b1b1577ab259c1ddf00956264836fa33052ef \
+    --hash=sha256:1a4cb2207ec3ac538fc728e4596e9e49aed6c4487a641071fb370c04a361e7bf \
+    --hash=sha256:2e052af8d7848e8bac92646584617503a08bb9b466cfa810a49ecd93e89b7ffa \
+    --hash=sha256:4ad4ab0d3367699d132e61b1cc382a0c640a7dba56536e5105508205ebbe8762 \
+    --hash=sha256:97ea4ff6114223c5e8ccce7e23cc6cd398b58c02f4e988e967aeea914fcb8030 \
+    --hash=sha256:e0ff0a81e6319575ffc8bf230b8df43f3f19f6fe96843e113e04c5ba9f7f3141 \
+    --hash=sha256:e6e6b1f8b0c4d2ca87e616ddc31d08330b36207e466357040f95269e5e0401c8
+    # via fuse-med-ml
 hf-xet==1.6.0 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64' \
     --hash=sha256:0e6e21fa3cdfcdcd76748564bf593870a5e013f47d97cf10aed63aa222cff5b7 \
     --hash=sha256:2e58454a340b3556dfa4972d5451aff4fba8dd42a236600ba1a1d2b1514f0fef \
@@ -790,6 +974,10 @@ hf-xet==1.6.0 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or
 hic-straw==1.3.1 \
     --hash=sha256:fb0f878127f6b1d096303c67793477c83fddf3f4a1a8e29a9d92952634989876
     # via bmfm-targets
+hpack==4.2.0 \
+    --hash=sha256:0895cfa3b5531fc65fe439c05eb65144f123bf7a394fcaa56aa423548d8e45c0 \
+    --hash=sha256:858ac0b02280fa582b5080d68db0899c62a80375e0e5413a74970c5e518b6986
+    # via h2
 httpcore==1.0.9 \
     --hash=sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55 \
     --hash=sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8
@@ -798,6 +986,7 @@ httpx==0.28.1 \
     --hash=sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc \
     --hash=sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad
     # via
+    #   blosc2
     #   diffusers
     #   huggingface-hub
 huey==3.3.4 \
@@ -811,6 +1000,7 @@ huggingface-hub==1.26.0 \
     #   accelerate
     #   bmfm-targets
     #   diffusers
+    #   fuse-med-ml
     #   peft
     #   segmentation-models-pytorch
     #   terrakit
@@ -822,8 +1012,14 @@ hydra-core==1.3.4 \
     --hash=sha256:ad0f7b05a0242255a8984d5a4ed2f6847f7b783ed727368a2c0155ec52d6c34c \
     --hash=sha256:e58683692904a09f1fdfffa1a9b86bfd94e215b59f1ee17e7cd7d92738090d33
     # via
+    #   biomed-multi-alignment
     #   bmfm-targets
+    #   fuse-med-ml
     #   lightly
+hyperframe==6.1.0 \
+    --hash=sha256:b03380493a519fce58ea5af42e4a42317bf9bd425596f7a0835ffce80f1a42e5 \
+    --hash=sha256:f630908a00854a7adeabd6382b43923a4c4cd4b821fcb527e6ab9e15382a3b08
+    # via h2
 idna==3.18 \
     --hash=sha256:7f952cbe720b688055e3f87de14f5c3e5fdaa8bc3928985c4077ca689de849a2 \
     --hash=sha256:ffb385a7e039654cef1ab9ef32c6fafe283c0c0467bba1d9029738ce4a14a848
@@ -844,6 +1040,18 @@ importlib-metadata==9.0.0 \
     #   diffusers
     #   mlflow-skinny
     #   tiledb-cloud
+iniconfig==2.3.0 \
+    --hash=sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730 \
+    --hash=sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12
+    # via pytest
+interface-meta==2.0.1 \
+    --hash=sha256:902bd9a95a12f195f15753a1080075d4eca7a2cb934fac7ac03c9e362b50796a \
+    --hash=sha256:f38016bef9a4429b6d0792d809be7b65e9781820c674bf7f463999086b6e6323
+    # via formulaic
+invoke==3.0.3 \
+    --hash=sha256:437b6a622223824380bfb4e64f612711a6b648c795f565efc8625af66fb57f0c \
+    --hash=sha256:f11327165e5cbb89b2ad1d88d3292b5113332c43b8553b494da435d6ec6f5053
+    # via paramiko
 ipyfilechooser==0.6.0 \
     --hash=sha256:41df9e4395a924f8e1b78e2804dbe5066dc3fdc233fb07fecfcdc2a0c9a7d8d3 \
     --hash=sha256:4555c24b30b819c91dc0ae5e6f7e4cf8f90e5cca531a9209a1fe4deee288d5c5
@@ -851,11 +1059,14 @@ ipyfilechooser==0.6.0 \
 ipykernel==7.3.0 \
     --hash=sha256:897eb64da762549ef610698fca5e9675195ec6ac8ec7f19d81ce1ca20c876057 \
     --hash=sha256:9acaaaf97d16355166e4085afe9d225bfbdf2b7ef520f9df3be8f2b248275e09
-    # via gridfm-datakit
+    # via
+    #   fuse-med-ml
+    #   gridfm-datakit
 ipython==9.16.1 \
     --hash=sha256:4acae635506f6d352d94c4899a19d5f85f8bc4d230932342dca556fdab1c69b4 \
     --hash=sha256:5a3d1f9a47ff216d6cf9cf863124f6a2c1a198d1354c546a4d24a370a283b64c
     # via
+    #   fuse-med-ml
     #   ipykernel
     #   ipywidgets
 ipython-pygments-lexers==1.1.1 \
@@ -905,6 +1116,7 @@ jsonargparse==4.50.0 \
     --hash=sha256:b066f0d716767c77b9af58d7e9bb433c42135bd3ea2a4f12e04d6152f4cdf91f \
     --hash=sha256:c559a3991e66cf04d987899b5c1ec6a3de6dc544c44a7cad97cc4a4343066d9a
     # via
+    #   fuse-med-ml
     #   terrakit
     #   terratorch
     #   torchgeo
@@ -943,6 +1155,10 @@ jupyterlab-widgets==3.0.16 \
     --hash=sha256:423da05071d55cf27a9e602216d35a3a65a3e41cdf9c5d3b643b814ce38c19e0 \
     --hash=sha256:45fa36d9c6422cf2559198e4db481aa243c7a32d9926b500781c830c80f7ecf8
     # via ipywidgets
+keras==3.15.1 \
+    --hash=sha256:836460e480930acbd19bb7a17e62f9ecad40e8a9af9a651fc8d0586a96d27e20 \
+    --hash=sha256:92ae7c1dd7f61041953dc2d42253181ee099086f0b58ae36fcf98147a6f08a29
+    # via tensorflow
 kiwisolver==1.5.0 \
     --hash=sha256:0b85aad90cea8ac6797a53b5d5f2e967334fa4d1149f031c4537569972596cb8 \
     --hash=sha256:0bf3acf1419fa93064a4c2189ac0b58e3be7872bf6ee6177b0d4c63dc4cea276 \
@@ -1026,6 +1242,22 @@ legacy-api-wrap==1.5 \
     # via
     #   anndata
     #   scanpy
+libclang==18.1.1 \
+    --hash=sha256:0b2e143f0fac830156feb56f9231ff8338c20aecfe72b4ffe96f19e5a1dbb69a \
+    --hash=sha256:3f0e1f49f04d3cd198985fea0511576b0aee16f9ff0e0f0cad7f9c57ec3c20e8 \
+    --hash=sha256:4dd2d3b82fab35e2bf9ca717d7b63ac990a3519c7e312f19fa8e86dcc712f7fb \
+    --hash=sha256:54dda940a4a0491a9d1532bf071ea3ef26e6dbaf03b5000ed94dd7174e8f9592 \
+    --hash=sha256:69f8eb8f65c279e765ffd28aaa7e9e364c776c17618af8bff22a8df58677ff4f \
+    --hash=sha256:6f14c3f194704e5d09769108f03185fce7acaf1d1ae4bbb2f30a72c2400cb7c5 \
+    --hash=sha256:83ce5045d101b669ac38e6da8e58765f12da2d3aafb3b9b98d88b286a60964d8 \
+    --hash=sha256:a1214966d08d73d971287fc3ead8dfaf82eb07fb197680d8b3859dbbbbf78250 \
+    --hash=sha256:c533091d8a3bbf7460a00cb6c1a71da93bffe148f172c7d03b1c31fbf8aa2a0b \
+    --hash=sha256:cf4a99b05376513717ab5d82a0db832c56ccea4fd61a69dbb7bccf2dfb207dbe
+    # via tensorflow
+lifelines==0.30.3 \
+    --hash=sha256:44802480a28d6cb836c7fea4a54ec0ba220eb31c6d7444589637a8bd66066e8c \
+    --hash=sha256:acd1e0ecada4280c7bb2948f39c760a0f9158a57d752c8ca29f984a86c698b7f
+    # via fuse-med-ml
 lightly==1.5.22 \
     --hash=sha256:58694433dd85ec371cb532dba3fea9465009d36e4afac67e53dbf464dba69e2a \
     --hash=sha256:7bb8939976ea5e8fabb20d049812700d51e44f6461f15510a784afd1252a3dbd
@@ -1072,6 +1304,10 @@ locket==1.0.0 \
     --hash=sha256:5c0d4c052a8bbbf750e056a8e65ccd309086f4f0f18a2eac306a8dfa4112a632 \
     --hash=sha256:b6c819a722f7b6bd955b80781788e4a66a55628b858d347536b7e81325a3a5e3
     # via partd
+loguru==0.7.3 \
+    --hash=sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6 \
+    --hash=sha256:31a33c10c8e1e10422bfd431aeb5d351c7cf7fa671e3c4df004162264b28220c
+    # via x-transformers
 mako==1.4.1 \
     --hash=sha256:a359d9a94a541213958742b2698d0a7757bb83551767bc468a74b9905aba9617 \
     --hash=sha256:d7904710b662996425a21627710c4777c45053146942cf8a7aebf757c92b8c27
@@ -1154,7 +1390,9 @@ matplotlib==3.11.1 \
     # via
     #   captum
     #   contextily
+    #   fuse-med-ml
     #   gridfm-datakit
+    #   lifelines
     #   mlflow
     #   scanpy
     #   seaborn
@@ -1177,6 +1415,26 @@ mercantile==1.2.1 \
     --hash=sha256:30f457a73ee88261aab787b7069d85961a5703bb09dc57a170190bc042cd023f \
     --hash=sha256:fa3c6db15daffd58454ac198b31887519a19caccee3f9d63d17ae7ff61b3b56b
     # via contextily
+ml-dtypes==0.5.4 \
+    --hash=sha256:304ad47faa395415b9ccbcc06a0350800bc50eda70f0e45326796e27c62f18b6 \
+    --hash=sha256:35f29491a3e478407f7047b8a4834e4640a77d2737e0b294d049746507af5175 \
+    --hash=sha256:3bbbe120b915090d9dd1375e4684dd17a20a2491ef25d640a908281da85e73f1 \
+    --hash=sha256:531eff30e4d368cb6255bc2328d070e35836aa4f282a0fb5f3a0cd7260257298 \
+    --hash=sha256:533ce891ba774eabf607172254f2e7260ba5f57bdd64030c9a4fcfbd99815d0d \
+    --hash=sha256:6a0df4223b514d799b8a1629c65ddc351b3efa833ccf7f8ea0cf654a61d1e35d \
+    --hash=sha256:8ab06a50fb9bf9666dd0fe5dfb4676fa2b0ac0f31ecff72a6c3af8e22c063453 \
+    --hash=sha256:8c760d85a2f82e2bed75867079188c9d18dae2ee77c25a54d60e9cc79be1bc48 \
+    --hash=sha256:9ad459e99793fa6e13bd5b7e6792c8f9190b4e5a1b45c63aba14a4d0a7f1d5ff \
+    --hash=sha256:9bad06436568442575beb2d03389aa7456c690a5b05892c471215bfd8cf39460 \
+    --hash=sha256:a174837a64f5b16cab6f368171a1a03a27936b31699d167684073ff1c4237dac \
+    --hash=sha256:a7f7c643e8b1320fd958bf098aa7ecf70623a42ec5154e3be3be673f4c34d900 \
+    --hash=sha256:c1a953995cccb9e25a4ae19e34316671e4e2edaebe4cf538229b1fc7109087b7 \
+    --hash=sha256:cb73dccfc991691c444acc8c0012bee8f2470da826a92e3a20bb333b1a7894e6 \
+    --hash=sha256:ce756d3a10d0c4067172804c9cc276ba9cc0ff47af9078ad439b075d1abdc29b \
+    --hash=sha256:f21c9219ef48ca5ee78402d5cc831bd58ea27ce89beda894428bc67a52da5328
+    # via
+    #   keras
+    #   tensorflow
 mlflow==3.15.1 \
     --hash=sha256:6177b02c442d7d6ab3ad752daa826db9cf993e255450fb4b00ea8b7b5539c01d \
     --hash=sha256:c91f78d304d8ef825869ea07e638c73a2850660f0d9f098993bacecc359f8a75
@@ -1197,6 +1455,31 @@ mpmath==1.3.0 \
     --hash=sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f \
     --hash=sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c
     # via sympy
+msgpack==1.2.1 \
+    --hash=sha256:020e881a764b20d8d7ca1a54fc01b8175519d108e3c3f194fddc200bda95951a \
+    --hash=sha256:04c721c2c7448767e9e3f2520a475663d8ee0f09c31890f6d2bd70fd636a9647 \
+    --hash=sha256:0a70e3cf2804a300d921bb0940426e35f4e489a23adfb77a808892241db0a064 \
+    --hash=sha256:0c0d9802354507bcba62af19c17918e3eb437cc25e6f50657d511b5856a77aac \
+    --hash=sha256:1233ee2dd0cefba127583de50ea654677277047d238303521db35def3d7b2e7c \
+    --hash=sha256:2ef59c659f289eddf8aa6623823f19fa2f40a4029266889eac7a2505dd210c35 \
+    --hash=sha256:33f14fba63278b714efe6ad07e50ea5f03d91537aa6a1c5f1ceca4cf44013ca9 \
+    --hash=sha256:4202c74688ca06591f78cb18988228bd4cca2cc75d57b60008372892d2f1e6e6 \
+    --hash=sha256:4227224aaec8f7fbcbfbd4272319347b2bb4030366502600f8c45588c5187b07 \
+    --hash=sha256:491cc39455ca765fad51fb451bf2915eb2cf41192ab5801ce8d67c1d614fe056 \
+    --hash=sha256:5c24aa15d5963051e1a5c62b12c50cd705992502b5ec1f3bece6046f33c9fc24 \
+    --hash=sha256:60926b75d00c8e816ef98f3034f484a8bc64242d66839cef4cf7e503142316a0 \
+    --hash=sha256:6d09badf350af2be9d189184e04e64cf54ad93569ab3d96fca58bd3e84aad707 \
+    --hash=sha256:787c9bebb5833e8f6fc8abca3c0597683d8d87f56a8842b6b89c75a5f3176e2d \
+    --hash=sha256:85f57e960d877f2977f6430896191b04a21f8901b3b4baf2e4604329f4db5402 \
+    --hash=sha256:8b267ce94efb76fbd1b3373511420074ee3187f0f7811bf394531de13294735a \
+    --hash=sha256:afc5febcd4c99effbc02b528e49d6fd0760b2b7d48c05239e345a5fa6e743d9a \
+    --hash=sha256:d3567748a5107cb40cdf66a275430c2f87c07777698f4bfd25c35f44d533258c \
+    --hash=sha256:dc871b997a9370d855b7394465f2f350e847a5b806dd38dcc9c989e7d87da155 \
+    --hash=sha256:e3dc2feb0876209d9c38aa56cb1de169bd6c4348f1aa48271f241226590993e6 \
+    --hash=sha256:e4f1d0f8f98ade9634e01fb704a408f9336c0a8f1117b369f5db83dc7551d8b1 \
+    --hash=sha256:f02cf17a6ca1abe29b5f980644f7551f94d71f2011509b26d8625ce038f0df64 \
+    --hash=sha256:f310233ef7fb9c14e201c93639fe5f5260b005f56f0b29048e999c30935596cc
+    # via blosc2
 multidict==6.7.1 \
     --hash=sha256:03ede2a6ffbe8ef936b92cb4529f27f42be7f56afcdab5ab739cd5f27fb1cbf9 \
     --hash=sha256:0b4c48648d7649c9335cf1927a8b87fa692de3dcb15faa676c6a6f1f1aabda43 \
@@ -1266,10 +1549,15 @@ mypy-extensions==1.1.0 \
     --hash=sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505 \
     --hash=sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558
     # via typing-inspect
+namex==0.1.0 \
+    --hash=sha256:117f03ccd302cc48e3f5c58a296838f6b89c83455ab8683a1e85f2a430aa4306 \
+    --hash=sha256:e2012a474502f1e2251267062aae3114611f07df4224b6e06334c57b0f2ce87c
+    # via keras
 narwhals==2.24.0 \
     --hash=sha256:42fdedf44e5b2ca7505630d45b4ac3058f38d8485cba9fe1652ca23152df7489 \
     --hash=sha256:b5c0f684ccd9d7475b564111e319a4964abcf2baf79d3cf6b1003d06ac9b828d
     # via
+    #   formulaic
     #   plotly
     #   scikit-learn
 natsort==8.4.0 \
@@ -1284,6 +1572,33 @@ nbformat==5.10.4 \
     # via
     #   gridfm-datakit
     #   gridfm-graphkit
+ndindex==1.10.1 \
+    --hash=sha256:03cf1e6cdac876bd8fc92d3b65bb223496b1581d10eab3ba113f7c195121a959 \
+    --hash=sha256:046c1e88d46b2bd2fd3483e06d27b4e85132b55bc693f2fca2db0bb56eea1e78 \
+    --hash=sha256:08bfdc1f7a0b408d15b3ce61d141ebbebdb47a25341967e425e104c5bd512a5c \
+    --hash=sha256:0f6113c1f031248f8818cbee1aa92aa3c9472b7701debcce9fddebcd2f610f11 \
+    --hash=sha256:157b5c34a1b779f5d27b790d9bd7e7b156d284e76be83c591a3ba003984f4956 \
+    --hash=sha256:23d35696f802548143b5cc199bf2f171efb0061aa7934959251dd3bae56d038c \
+    --hash=sha256:346a4bf09f5771548665c8206e81daadb6b9925d409746e709894bdd98adc701 \
+    --hash=sha256:3b0d9ce2c8488444499ab6d40e92e09867bf4413f5cf04c01635de923f44aa67 \
+    --hash=sha256:5c026dbbf2455d97ce6456d8a50b349aee8fefa11027d020638c89e9be2c9c4c \
+    --hash=sha256:6928e47fb008903f2e41309b7ff1e59b16abbcd59e2e945454571c28b2433c9e \
+    --hash=sha256:72af787dcee3661f36fff9d144d989aacefe32e2c8b51ceef9babd46afb93a18 \
+    --hash=sha256:752e78a5e87911ded117c57a7246596f26c9c6da066de3c2b533b3db694949bb \
+    --hash=sha256:78bfe25941d2dac406391ddd9baf0b0fce163807b98ecc2c47a3030ee8466319 \
+    --hash=sha256:7da34a78410c14341d5fff73be5ce924bd36500bf7f640fc59b8607d3a0df95e \
+    --hash=sha256:87f83e8c35a7f49a68cd3a3054c406e6c22f8c1315f3905f7a778c657669187e \
+    --hash=sha256:9599fcb7411ffe601c367f0a5d4bc0ed588e3e7d9dc7604bdb32c8f669456b9e \
+    --hash=sha256:a91e1a0398120233d5c3b23ccb2d4b78e970d66136f1a7221fa9a53873c3d5c5 \
+    --hash=sha256:c9dd58d91220b1c1fe516324bfcf4114566c98e84b1cbbe416abe345c75bd557 \
+    --hash=sha256:cb76e0f3f235d8b1c768b17e771de48775d281713795c3aa045e8114ad61bdda \
+    --hash=sha256:cf9e05986b2eb8c5993bce0f911d6cedd15bda30b5e35dd354b1ad1f4cc3599d \
+    --hash=sha256:d0ebdba2fade3f6916fe21fd49e2a0935af4f58c56100a60f3f2eb26e20baee7 \
+    --hash=sha256:e69a2cb1ac7be955c3c77f1def83f410775a81525c9ce2d4c0a3f2a61589ed47 \
+    --hash=sha256:ef3ef22390a892d16286505083ee5b326317b21c255a0c7f744b1290a0b964a6 \
+    --hash=sha256:f99b3e89220da3244d03c9c5473669c7107d361c129fd9b064622744dee1ce15 \
+    --hash=sha256:fa60637dfae1ee3fc057e420a52cc4ace38cf2c0d1a0451af2a3cba84d281842
+    # via blosc2
 nest-asyncio==1.6.0 \
     --hash=sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe \
     --hash=sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c
@@ -1311,6 +1626,10 @@ networkx==3.6.1 \
     #   scanpy
     #   scikit-image
     #   torch
+nibabel==5.4.2 \
+    --hash=sha256:553482c5f1e1034fc312edf6fb7f32236c0056439845d1c29293b7e8c98d4854 \
+    --hash=sha256:d5f4b9076a13178ae7f7acf18c8dbd503ee1c4d5c0c23b85df7be87efcbb49da
+    # via fuse-med-ml
 numba==0.65.0 \
     --hash=sha256:59bb9f2bb9f1238dfd8e927ba50645c18ae769fef4f3d58ea0ea22a2683b91f5 \
     --hash=sha256:6254e73b9c929dc736a1fbd3d6f5680789709a5067cae1fa7198707385129c04 \
@@ -1358,7 +1677,10 @@ numexpr==2.14.2 \
     --hash=sha256:dd905922d7dce457947d54b84c7ac345cef37332b724445e159a5a1a2080ce2b \
     --hash=sha256:e7144e83ea9e581f2273e0304f15836736c4e470e2bd2e378ce617662a1ca278 \
     --hash=sha256:fd2f5882a66a7792aa6614c68831aa20085b499d41422aedd001080624ebb14c
-    # via bmfm-targets
+    # via
+    #   blosc2
+    #   bmfm-targets
+    #   tables
 numpy==2.4.6 \
     --hash=sha256:001fbb8e08d942dd57599e781f2472269ee7f2755fae407b4f67b2f0b17da3f1 \
     --hash=sha256:043191bfa8eab18c776647b62723ac9dddece59743b13f49b2016094129c2b3f \
@@ -1398,29 +1720,39 @@ numpy==2.4.6 \
     #   albucore
     #   albumentations
     #   anndata
+    #   autograd
+    #   blosc2
     #   bmfm-targets
     #   captum
     #   cellxgene-census
     #   cftime
+    #   choix
     #   clearml
     #   contourpy
     #   dask
     #   diffusers
+    #   einx
     #   fast-array-utils
     #   focal-loss-torch
     #   folium
+    #   formulaic
+    #   fuse-med-ml
     #   geopandas
     #   gridfm-datakit
     #   gridfm-graphkit
     #   h5py
     #   imageio
+    #   keras
+    #   lifelines
     #   lightly
     #   lightly-utils
     #   litdata
     #   matplotlib
     #   matpowercaseframes
+    #   ml-dtypes
     #   mlflow
     #   netcdf4
+    #   nibabel
     #   numba
     #   numcodecs
     #   numexpr
@@ -1447,8 +1779,10 @@ numpy==2.4.6 \
     #   somacore
     #   stackstac
     #   statsmodels
+    #   tables
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   terrakit
     #   terratorch
     #   tifffile
@@ -1574,6 +1908,7 @@ omegaconf==2.3.1 \
     --hash=sha256:e5e7de64aeebeddaf8e6d3f7a783b32ac2a01c0fbd9c878012caecb891a1f42a
     # via
     #   bmfm-targets
+    #   fuse-med-ml
     #   hydra-core
 opencv-python-headless==4.14.0.94 \
     --hash=sha256:1777f43c9fa064f54b916ad70d944b4fde0a644a17e49f04a966bb24a4b5f1e1 \
@@ -1615,11 +1950,56 @@ opentelemetry-semantic-conventions==0.65b0 \
 opt-einsum==3.4.0 \
     --hash=sha256:69bb92469f86a1565195ece4ac0323943e83477171b91d24c35afe028a90d7cd \
     --hash=sha256:96ca72f1b886d148241348783498194c577fa30a8faac108586b14f1ba4473ac
-    # via gridfm-graphkit
+    # via
+    #   gridfm-graphkit
+    #   tensorflow
+optree==0.19.1 \
+    --hash=sha256:03faa8e23fdaf3a18f9a1568c2c0eb0641a6aa05baf3a20639bd11fb34664700 \
+    --hash=sha256:06f5c8a4cf356a1a276ce5cec1be44719ed260690f79c036d04b4d427e801258 \
+    --hash=sha256:08ccec0ee5a565eb5aa4fe30383016a358627ea23d968ec8ab28b1f2ce4ce3d8 \
+    --hash=sha256:1c5d21176b670407f4555aae40711668832599c4fb0627000c5ce3ed0d6e2dae \
+    --hash=sha256:39a006735d2a0a68751a3bc33d670184fddcd86db63b0293e1e819739e8105e4 \
+    --hash=sha256:4497d1c9197b8c6842e511368163d318ce536521ebdcff8bebb7551dcdfac532 \
+    --hash=sha256:544b70958dbd7e732bc6874e0180c609c9052115937d0ec28123bb49c1a574aa \
+    --hash=sha256:5d9d198343e1e6ced18bef0cbff84091c1877964fc4a121df33f18840e073a01 \
+    --hash=sha256:672588408906051d3e9a99aca6c0af93c6e0b638137a701418088eaa0bb6c719 \
+    --hash=sha256:6f0b1efc177bed6495f78d39d5aa495ccb31cc20bcf64bb1b806ca4c919f4049 \
+    --hash=sha256:76b3e9e5d37e6b05ec82fff91758c8c0e27e159b35faea4b33d5eb975d720257 \
+    --hash=sha256:7a1202371d9fe3aa75f3e886b1f871aac4991a655aadb65e54f58a3ae9388ab2 \
+    --hash=sha256:7d934f240b109c6891dd06b2e30400b123b8a4b6ed31dcd0db2ae2378d30a6e8 \
+    --hash=sha256:9690c132822d9dee479cf7dff8cc52a67c8af42a4f7529d21f0f4f1d99e4c84e \
+    --hash=sha256:96e5c7c3b9144f08ae40c3d9848cfbcfa36b6bead0f8215ad071d5922ee6c4a5 \
+    --hash=sha256:9870d33ec50cca0c46c2b431cea24c6247457da15fd4ad66ccb8ab78145c1490 \
+    --hash=sha256:9dde5b756946c1f1458aeab248a7a9b0c01bb06b5787de9f06d52ad38b745557 \
+    --hash=sha256:a33bd23fc5c67ecb9ff491b75fde10cd9b53f47f8a876de842090e8c7a2437e1 \
+    --hash=sha256:a9b9c7e9148ec470124dc4c1d1cd1485dbeb35973357b5911b181a79090426d2 \
+    --hash=sha256:aa0845b725bcd0029e179cf9b4bc2cc016c7358e56fc7c0d2c43bf4d514c96cf \
+    --hash=sha256:ab8ad9803376d553a2958471b6bb6842b7e15888e19cc6aeb76da96c6afd948d \
+    --hash=sha256:afd4abeb2783b2367093287bc6268ac9af244b20c8d9b01696ccfe817483b66c \
+    --hash=sha256:b9120510d3f951e268e417a3f64f335bc1c539e1e80bff2129ddc6fb60ac7b56 \
+    --hash=sha256:b964bcdb5cfe367cdf56447e80ba5a49123098d8c4e8e68b41c20890eec6e58e \
+    --hash=sha256:d16cef4d0555d49ce221d80249f1285a2d3faf932e451c3ce6cb8ccb6a846767 \
+    --hash=sha256:d2cb43c36638f469f5d8f4cf638e914de90c62242d8bed29f1b4487e0346ab94 \
+    --hash=sha256:d41ccc4c20bfeae01d1d221c057a6d026e84e32229664952eddcdbe4b9b71417 \
+    --hash=sha256:dc2db0b449baff53aa7e583306101de0ade5e5ae9e6fce78400eb2319bbd23dc \
+    --hash=sha256:ddeefb7ca799c09647e332ebc1a5f6c09888a5a0e51f2dff4ca55e65b42a8c14 \
+    --hash=sha256:e0f02600832ab8d0f6c934dcb5c339e17a36938d477641a45798e02625ebe107 \
+    --hash=sha256:e70faa00ab69331f49f8337d45021bed09ae2265d1db72eea9d7817af2b73c64 \
+    --hash=sha256:e757079d44a00319447f43df5c51e55bf9b62d9f05eea0e2db5ff7c7ca5ec71d \
+    --hash=sha256:f0ce49f64f804f7f35f2f9c2a21e3ba94c090199fccdcfd40e3ded4426c5c175 \
+    --hash=sha256:f10d58c1a17e1b32f9d9b5e1b9d1ad964d99c1113d9df0b9f62f2fe7dde19909 \
+    --hash=sha256:f144cfd65fb17c6aa2c51818614eb009e6052d3d6ace91f7e570b1318cdcac4c \
+    --hash=sha256:f1d7838e8b1b62258abd73a5911afad1153ed76822070558c3ba7e0bb5b44192 \
+    --hash=sha256:f658fa46305b2bdccdc5bb2cb07818aeaef88a1085499deda5be48a0a58d2971
+    # via keras
 orderedmultidict==1.0.2 \
     --hash=sha256:16a7ae8432e02cc987d2d6d5af2df5938258f87c870675c73ee77a0920e6f4a6 \
     --hash=sha256:ab5044c1dca4226ae4c28524cfc5cc4c939f0b49e978efa46a6ad6468049f79b
     # via furl
+orderly-set==5.5.0 \
+    --hash=sha256:46f0b801948e98f427b412fcabb831677194c05c3b699b80de260374baa0b1e7 \
+    --hash=sha256:e87185c8e4d8afa64e7f8160ee2c542a475b738bc891dc3f58102e654125e6ce
+    # via deepdiff
 packaging==26.3 \
     --hash=sha256:94edc256424af38762eb31306eed28beb9f0efc50a8837492c9d6fd6004aed79 \
     --hash=sha256:d7193f7c8e4e93f444fde0262bf90af30e16fa0ad0ad44cb553c87339b23cd1c
@@ -1633,6 +2013,7 @@ packaging==26.3 \
     #   huggingface-hub
     #   hydra-core
     #   ipykernel
+    #   keras
     #   kornia
     #   lazy-loader
     #   lightning
@@ -1641,22 +2022,28 @@ packaging==26.3 \
     #   matplotlib
     #   mlflow-skinny
     #   mlflow-tracing
+    #   nibabel
     #   pandera
     #   peft
     #   plotly
     #   pyogrio
+    #   pytest
     #   pytorch-lightning
     #   rioxarray
     #   scanpy
     #   scikit-image
     #   skops
     #   statsmodels
+    #   tables
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
     #   tiledb
     #   tiledb-cloud
     #   torchmetrics
     #   transformers
+    #   wheel
+    #   x-transformers
     #   xarray
     #   zarr
 pandas==2.3.3 \
@@ -1684,9 +2071,12 @@ pandas==2.3.3 \
     # via
     #   anndata
     #   bmfm-targets
+    #   formulaic
+    #   fuse-med-ml
     #   geopandas
     #   gridfm-datakit
     #   gridfm-graphkit
+    #   lifelines
     #   matpowercaseframes
     #   mlflow
     #   rdata
@@ -1704,6 +2094,10 @@ pandera==0.32.1 \
     --hash=sha256:1a17a3ffa906174d19207715f4f082ec3db3709647927ad8c095c147d74d8454 \
     --hash=sha256:72ecd74226847abf0f0437c05f7f10cc8368e306d88a2acc78fa93762c5a0a02
     # via rnanorm
+paramiko==5.0.0 \
+    --hash=sha256:36763b5b95c2a0dcfdf1abc48e48156ee425b21efe2f0e787c2dd5a95c0e5e79 \
+    --hash=sha256:b7044611c30140d9a75261653210e2002977b71a0497ff3ba0d98d7edbf62f7c
+    # via fuse-med-ml
 parso==0.8.7 \
     --hash=sha256:a8926eb2a1b915486941fdbd31e86a4baf88fe8c210f25f2f35ecec5b574ca1c \
     --hash=sha256:eaaac4c9fdd5e9e8852dc778d2d7405897ec510f2a298071453e5e3a07914bb1
@@ -1729,7 +2123,9 @@ patsy==1.0.2 \
 peft==0.20.0 \
     --hash=sha256:0fbba16ffebfad3de96e06f2da6860fd860292324b85b6141909fa1e26ea9233 \
     --hash=sha256:4769c8093a4ca145fd6fb3fd4dd50449675f5fe46434ad1e98b285a132d4b1d0
-    # via bmfm-targets
+    # via
+    #   biomed-multi-alignment
+    #   bmfm-targets
 pexpect==4.9.0 ; sys_platform != 'emscripten' and sys_platform != 'win32' \
     --hash=sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 \
     --hash=sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f
@@ -1783,6 +2179,10 @@ plotly==6.9.0 \
     # via
     #   gridfm-datakit
     #   gridfm-graphkit
+pluggy==1.6.0 \
+    --hash=sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3 \
+    --hash=sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746
+    # via pytest
 prettytable==3.18.0 \
     --hash=sha256:439217116152244369caf3d9f1caf2f9fe29b03bd79e88d2928c8e718c95d680 \
     --hash=sha256:b3346e0e6f79180833aebaac088ae926340586cf6d7d991b9eb125b65f72313a
@@ -1864,6 +2264,7 @@ protobuf==6.33.6 \
     #   opentelemetry-proto
     #   tensorboard
     #   tensorboardx
+    #   tensorflow
 psutil==7.2.2 \
     --hash=sha256:0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372 \
     --hash=sha256:076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9 \
@@ -1884,6 +2285,7 @@ psutil==7.2.2 \
     #   accelerate
     #   cellxgene-census
     #   clearml
+    #   fuse-med-ml
     #   ipykernel
     #   ipython
     #   peft
@@ -1897,6 +2299,10 @@ pure-eval==0.2.3 \
     --hash=sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0 \
     --hash=sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42
     # via stack-data
+py-cpuinfo==9.0.0 \
+    --hash=sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690 \
+    --hash=sha256:859625bc251f64e21f077d099d4162689c762b5d6a4c3c97553d56241c9674d5
+    # via tables
 pyaml==26.7.0 \
     --hash=sha256:11cda3a796efc6dbce0d56836be56cfd26289dad07bcd78e9904086729929c93 \
     --hash=sha256:cfa382780c43ae660669b87d394d550a41856ef175f5749f51f753e12d7077ac
@@ -1963,7 +2369,9 @@ pycocotools==2.0.11 \
     --hash=sha256:f7eb43b79448476b094240450420b7425d06e297880144b8ea6f01e9b4340e43 \
     --hash=sha256:fd72b9734e6084b217c1fc3945bfd4ec05bdc75a44e4f0c461a91442bb804973 \
     --hash=sha256:ffe806ce535f5996445188f9a35643791dc54beabc61bd81e2b03367356d604f
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   terratorch
 pycparser==3.0 ; (implementation_name != 'PyPy' and platform_python_implementation != 'PyPy') or (implementation_name == 'pypy' and platform_python_implementation == 'PyPy') \
     --hash=sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29 \
     --hash=sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992
@@ -1973,6 +2381,7 @@ pydantic==2.13.4 \
     --hash=sha256:c40756b57adaa8b1efeeced5c196f3f3b7c435f90e84ea7f443901bec8099ef6
     # via
     #   albumentations
+    #   blosc2
     #   bmfm-targets
     #   fastapi
     #   lightly
@@ -2030,11 +2439,27 @@ pygments==2.20.0 \
     # via
     #   ipython
     #   ipython-pygments-lexers
+    #   pytest
     #   rich
 pyjwt==2.9.0 \
     --hash=sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850 \
     --hash=sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c
     # via clearml
+pynacl==1.6.2 \
+    --hash=sha256:018494d6d696ae03c7e656e5e74cdfd8ea1326962cc401bcf018f1ed8436811c \
+    --hash=sha256:22de65bb9010a725b0dac248f353bb072969c94fa8d6b1f34b87d7953cf7bbe4 \
+    --hash=sha256:26bfcd00dcf2cf160f122186af731ae30ab120c18e8375684ec2670dccd28130 \
+    --hash=sha256:46065496ab748469cdd999246d17e301b2c24ae2fdf739132e580a0e94c94a87 \
+    --hash=sha256:5811c72b473b2f38f7e2a3dc4f8642e3a3e9b5e7317266e4ced1fba85cae41aa \
+    --hash=sha256:62985f233210dee6548c223301b6c25440852e13d59a8b81490203c3227c5ba0 \
+    --hash=sha256:68be3a09455743ff9505491220b64440ced8973fe930f270c8e07ccfa25b1f9e \
+    --hash=sha256:834a43af110f743a754448463e8fd61259cd4ab5bbedcf70f9dabad1d28a394c \
+    --hash=sha256:8845c0631c0be43abdd865511c41eab235e0be69c81dc66a50911594198679b0 \
+    --hash=sha256:8a66d6fb6ae7661c58995f9c6435bda2b1e68b54b598a6a10247bfcdadac996c \
+    --hash=sha256:8b097553b380236d51ed11356c953bf8ce36a29a3e596e934ecabe76c985a577 \
+    --hash=sha256:c8a231e36ec2cab018c4ad4358c386e36eede0319a0c41fed24f840b1dac59f6 \
+    --hash=sha256:c949ea47e4206af7c8f604b8278093b674f7c79ed0d4719cc836902bf4517465
+    # via paramiko
 pynndescent==0.6.0 \
     --hash=sha256:7ffde0fb5b400741e055a9f7d377e3702e02250616834231f6c209e39aac24f5 \
     --hash=sha256:dc8c74844e4c7f5cbd1e0cd6909da86fdc789e6ff4997336e344779c3d5538ef
@@ -2236,6 +2661,10 @@ pystac-ext-xarray-assets==1.0.0 \
     --hash=sha256:a31e90e7e9bc5ae191e7449df28c39857c818e8c1cf2c09a2eceaa7c6e13241c \
     --hash=sha256:da4f4877c018d531b6b5c45f20bc64842f14587ae86bac8d2acf110804c773d1
     # via pystac
+pytest==9.1.1 \
+    --hash=sha256:1088fbde8f2b49d95a549a195707afa7a76a3ce9bcadc26b6d71f0ffda5fe313 \
+    --hash=sha256:37a86b45efb9a47a61a36449063e8e18d0cab3161329fc099eb21783169c4f0c
+    # via biomed-multi-alignment
 python-box==7.4.1 \
     --hash=sha256:2ca9a18fd15326bc267e9cc7e0e6e3a0cb78d11507940f43f687adf7e156d882 \
     --hash=sha256:615da3fafd41572aec1b905832555c0ea08b6fbc27cc917356e257a9a5721af7 \
@@ -2276,6 +2705,7 @@ pytorch-lightning==2.6.5 \
     --hash=sha256:62d9c8549b2278fedc3364f0a5607a56c6063d18635008f8cf3fae8d802b0d76
     # via
     #   bmfm-targets
+    #   fuse-med-ml
     #   lightly
     #   lightning
 pytz==2026.3.post1 \
@@ -2472,6 +2902,7 @@ requests==2.34.2 \
     #   pystac-client
     #   requests-oauthlib
     #   sentinelhub
+    #   tensorflow
     #   terrakit
     #   torch-geometric
     #   torchdata
@@ -2483,7 +2914,9 @@ rich==15.0.0 \
     --hash=sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb \
     --hash=sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36
     # via
+    #   blosc2
     #   bmfm-targets
+    #   keras
     #   terratorch
     #   typer
 rioxarray==0.23.0 \
@@ -2615,6 +3048,7 @@ scikit-learn==1.9.0 \
     --hash=sha256:da76d09304a4706db7cc1e3ebaa3b6b98a67365cc11d2996c4f1e58ba47df714
     # via
     #   cellxgene-census
+    #   fuse-med-ml
     #   mlflow
     #   pynndescent
     #   rnanorm
@@ -2660,9 +3094,14 @@ scipy==1.18.0 \
     # via
     #   albumentations
     #   anndata
+    #   autograd-gamma
     #   bmfm-targets
+    #   choix
     #   fast-array-utils
+    #   formulaic
+    #   fuse-med-ml
     #   gridfm-datakit
+    #   lifelines
     #   mlflow
     #   pynndescent
     #   rioxarray
@@ -2712,6 +3151,7 @@ setuptools==80.10.2 \
     --hash=sha256:95b30ddfb717250edb492926c92b5221f7ef3fbcc2b07579bcd4a27da21d0173
     # via
     #   tensorboard
+    #   tensorflow
     #   torch
 shapely==2.1.2 \
     --hash=sha256:01d0d304b25634d60bd7cf291828119ab55a3bab87dc4af1e44b07fb225f188b \
@@ -2787,12 +3227,15 @@ six==1.17.0 \
     --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
     --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
     # via
+    #   astunparse
     #   clearml
     #   furl
+    #   google-pasta
     #   lightly
     #   orderedmultidict
     #   pathlib2
     #   python-dateutil
+    #   tensorflow
     #   tiledb-cloud
 skops==0.14.0 \
     --hash=sha256:60a5db78a9db46ccee2139a0ba13ab5afb1c96f4749b382e75a371291bbe3e36 \
@@ -2862,7 +3305,9 @@ statsmodels==0.14.6 \
     --hash=sha256:d8c00a42863e4f4733ac9d078bbfad816249c01451740e6f5053ecc7db6d6368 \
     --hash=sha256:f1c08befa85e93acc992b72a390ddb7bd876190f1360e61d10cf43833463bc9c \
     --hash=sha256:fe76140ae7adc5ff0e60a3f0d56f4fffef484efa803c3efebf2fcd734d72ecb5
-    # via scanpy
+    # via
+    #   fuse-med-ml
+    #   scanpy
 stringzilla==5.0.7 \
     --hash=sha256:00cf35c73405f9abff228297f9da010e36436fed9c157f05f7d3973ab48a7465 \
     --hash=sha256:023287ba3842b3040d98d8f5337e030a91ebfed95123ea48f46fbc862557afbc \
@@ -2907,7 +3352,21 @@ stringzilla==5.0.7 \
 sympy==1.14.0 \
     --hash=sha256:d3d3fe8df1e5a0b42f0e7bdf50541697dbe7d23746e894990c030e2b05e72517 \
     --hash=sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5
-    # via torch
+    # via
+    #   einx
+    #   torch
+tables==3.11.1 \
+    --hash=sha256:1e78fe190fdeb4afe430b79651bae2a4f341904eb85aa8dbafe5f1caee1c7f67 \
+    --hash=sha256:56bf6fb9132ead989b7e76695d7613d6d08f071a8019038d6565ba90c66b9f3e \
+    --hash=sha256:78abcf413091bc7c1e4e8c10fbbb438d1ac0b5a87436c5b972c3e8253871b6fb \
+    --hash=sha256:7fa6cb03f6fe55ae4f85e89ec5450e5c40cc4c52d8c3b60eb157a445c2219e89 \
+    --hash=sha256:eb30684c42a77bbecdef2b9c763c4372b0ddc9cc5bd8b2a2055f2042eee67217 \
+    --hash=sha256:f0367d2e3df0f10ea63ccf4279f3fe58e32ec481767320301a483e2b3cd83efc
+    # via fuse-med-ml
+tabulate==0.10.0 \
+    --hash=sha256:e2cfde8f79420f6deeffdeda9aaec3b6bc5abce947655d17ac662b126e48a60d \
+    --hash=sha256:f0b0622e567335c8fabaaa659f1b33bcb6ddfe2e496071b743aa113f8774f2d3
+    # via biomed-multi-alignment
 tacoreader==2.4.21 \
     --hash=sha256:485913e87484d9933081807ec3accfe65e98316a25a6f66c790a5e3d42514796 \
     --hash=sha256:63804e5b29b8660872aa6b17f6a001180acb7125d81a65b89294c76fd92eb495
@@ -2939,7 +3398,9 @@ tblib==3.2.2 \
     # via tiledb-cloud
 tensorboard==2.21.0 \
     --hash=sha256:7279316dcb6bd5bc391d623dea841531299cde1887310e8133bc34a996d32255
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   terratorch
 tensorboard-data-server==0.7.2 \
     --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
     --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
@@ -2949,10 +3410,23 @@ tensorboardx==2.6.5 \
     --hash=sha256:c10b891d00af306537cb8b58a039b2ba41571f0da06f433a41c4ca8d6abe1373 \
     --hash=sha256:ca176db3997ee8c07d2eb77381225956a3fd1c10c91beafab1f17069adc47017
     # via bmfm-targets
+tensorflow==2.21.0 \
+    --hash=sha256:27ba0682572b1e50a0db1ee74cfb787eafcfdb1b751bbbf401fed62fe32a92e0 \
+    --hash=sha256:56ecd7d47429acbe1df2694d50b75bf9fc3995ac92cb367cd9af6c4780ead712 \
+    --hash=sha256:76cccbe0a95d9392dee1ae501ae0656b6c73c1cac29a7f8f32d570e0670863f7 \
+    --hash=sha256:a10abdfb8b1189210c251021a3f153b7ccc52a8e6521351f3dc3331e8ba593e0 \
+    --hash=sha256:a145ed46c58192b7c3f9916d070caf4f6afc6dc7e5511f83dd97677f4c4947f4 \
+    --hash=sha256:b07d15737406533898e36c7ef7944b1be18e9028dc521b9229952c537bbc5552 \
+    --hash=sha256:b3b95643c4e70eb925839938fb35cbe142f317ec84af6844ee61513713bb13c0 \
+    --hash=sha256:e9d8da8dcab9650efb45f032ba70af2f016f907e6e0c6bda29dd101bba945406
+    # via biomed-multi-alignment
 termcolor==3.3.0 \
     --hash=sha256:348871ca648ec6a9a983a13ab626c0acce02f515b9e1983332b17af7979521c5 \
     --hash=sha256:cf642efadaf0a8ebbbf4bc7a31cec2f9b5f21a9f726f4ccbb08192c9c26f43a5
-    # via terratorch
+    # via
+    #   fuse-med-ml
+    #   tensorflow
+    #   terratorch
 terrakit==0.2.0 \
     --hash=sha256:683587a1f630ccbab5e345fdb2c8c0ee393aa450f0523b30ab1004aba1ca26a7 \
     --hash=sha256:e72951ceb6f4745554c47a633373de702caafde13690c440fbf8a16301b3508d
@@ -2964,7 +3438,9 @@ terratorch==1.2.10 \
 threadpoolctl==3.6.0 \
     --hash=sha256:43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb \
     --hash=sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e
-    # via scikit-learn
+    # via
+    #   blosc2
+    #   scikit-learn
 tifffile==2026.7.31 \
     --hash=sha256:79b1f4b1aba3ef3e6b6f1691a32abb62f5d7383faa52a12771c695232ba40bee \
     --hash=sha256:81adfa08012be1c478f99b83cda2f529eef8620cfbdf94fc41eef6f1d7b47dc5
@@ -3042,7 +3518,9 @@ tokenizers==0.22.2 \
     --hash=sha256:bfb88f22a209ff7b40a576d5324bf8286b519d7358663db21d6246fb17eea2d5 \
     --hash=sha256:c9ea31edff2968b44a88f97d784c2f16dc0729b8b143ed004699ebca91f05c48 \
     --hash=sha256:df6c4265b289083bf710dff49bc51ef252f9d5be33a45ee2bed151114a56207b
-    # via transformers
+    # via
+    #   fuse-med-ml
+    #   transformers
 tomli==2.4.1 \
     --hash=sha256:0d85819802132122da43cb86656f8d1f8c6587d54ae7dcaf30e90533028b49fe \
     --hash=sha256:136443dbd7e1dee43c68ac2694fde36b2849865fa258d39bf822c10e8068eac5 \
@@ -3100,6 +3578,7 @@ torch==2.11.0 \
     #   captum
     #   cellxgene-census
     #   focal-loss-torch
+    #   fuse-med-ml
     #   gridfm-graphkit
     #   kornia
     #   lightly
@@ -3111,10 +3590,17 @@ torch==2.11.0 \
     #   terratorch
     #   timm
     #   tokamind
+    #   torch-einops-utils
     #   torchdata
     #   torchgeo
     #   torchmetrics
     #   torchvision
+    #   vit-pytorch
+    #   x-transformers
+torch-einops-utils==0.1.12 \
+    --hash=sha256:9cbfe7e365d985c629a22830eea2541dcd990230a3e49a1916038938386b0bbe \
+    --hash=sha256:ab2b46a235a5ce6af0b29bff93ee83aecf4cacdb31cadc05de74eaf369708cd6
+    # via x-transformers
 torch-geometric==2.8.0.post1 \
     --hash=sha256:2c0c81666ec10f2132f6b4e0b6c57fc813f2c9f6b57599d7b7a799c614c22fbd \
     --hash=sha256:5d9841cbfa64eadc425e445767127d103dd52fdc5890548c6364986c9bc78029
@@ -3167,6 +3653,7 @@ torchvision==0.26.0 \
     --hash=sha256:d61a5abb6b42a0c0c311996c2ac4b83a94418a97182c83b055a2a4ae985e05aa \
     --hash=sha256:ebc043cc5a4f0bf22e7680806dbba37ffb19e70f6953bbb44ed1a90aeb5c9bea
     # via
+    #   fuse-med-ml
     #   gridfm-graphkit
     #   lightly
     #   litdata
@@ -3174,6 +3661,7 @@ torchvision==0.26.0 \
     #   terratorch
     #   timm
     #   torchgeo
+    #   vit-pytorch
 tornado==6.5.7 \
     --hash=sha256:148b2eb15c2c765a50796172c1e499649b35f30d2e3c3d3e15913cfa56bfb163 \
     --hash=sha256:66c513a76cda70d53907bc27cf1447557699c2e95aa48ba27a442ff61c3ddfc2 \
@@ -3194,6 +3682,7 @@ tqdm==4.70.0 \
     # via
     #   captum
     #   cdsapi
+    #   fuse-med-ml
     #   gdown
     #   gridfm-datakit
     #   huggingface-hub
@@ -3227,7 +3716,9 @@ transformers==5.14.1 \
     --hash=sha256:60d196c27781eacf8637e2b533f517582907ad6f9ae142046d6b69431a5b2173 \
     --hash=sha256:9db974c4079ede2d1a3ea7ca5a240df33f2cc26fc2b36ba64c5f2a4f43b6e725
     # via
+    #   biomed-multi-alignment
     #   bmfm-targets
+    #   fuse-med-ml
     #   peft
 triton==3.6.0 ; sys_platform == 'linux' \
     --hash=sha256:10c7f76c6e72d2ef08df639e3d0d30729112f47a56b0c81672edc05ee5116ac9 \
@@ -3262,6 +3753,7 @@ typing-extensions==4.16.0 \
     #   cellxgene-census
     #   ecmwf-datastores-client
     #   fastapi
+    #   formulaic
     #   graphene
     #   grpcio
     #   huggingface-hub
@@ -3269,10 +3761,12 @@ typing-extensions==4.16.0 \
     #   lightning
     #   lightning-utilities
     #   mlflow-skinny
+    #   nibabel
     #   obstore
     #   opentelemetry-api
     #   opentelemetry-sdk
     #   opentelemetry-semantic-conventions
+    #   optree
     #   pandera
     #   pydantic
     #   pydantic-core
@@ -3285,6 +3779,7 @@ typing-extensions==4.16.0 \
     #   somacore
     #   sqlalchemy
     #   starlette
+    #   tensorflow
     #   tiledb-cloud
     #   tiledb-vector-search
     #   tiledbsoma
@@ -3339,6 +3834,10 @@ uvicorn==0.52.1 \
     --hash=sha256:112ec661814189acbccd3f7b86460147cc065fc92c0821afa78918780e4354dd \
     --hash=sha256:e4403f9d93188cf9d1088e9f40e3acd12630e2df8675316704379a7fc20fff6a
     # via mlflow-skinny
+vit-pytorch==1.24.2 \
+    --hash=sha256:049b78b63981f67af4bb773e67c094b47d3a61c0b500959f66b6c223909cbfa2 \
+    --hash=sha256:77e7b9dbd034821b31064aeaf53f7bcd22c32a1eb70e1915d9681978a5af2d93
+    # via fuse-med-ml
 waitress==3.0.2 ; sys_platform == 'win32' \
     --hash=sha256:682aaaf2af0c44ada4abfb70ded36393f0e307f4ab9456a215ce0020baefc31f \
     --hash=sha256:c56d67fd6e87c2ee598b76abdd4e96cfad1f24cacdea5078d382b1f9d7b5ed2e
@@ -3356,10 +3855,21 @@ werkzeug==3.1.8 \
     #   flask
     #   flask-cors
     #   tensorboard
+wget==3.2 \
+    --hash=sha256:35e630eca2aa50ce998b9b1a127bb26b30dfee573702782aa982f875e3f16061
+    # via fuse-med-ml
+wheel==0.47.0 \
+    --hash=sha256:212281cab4dff978f6cedd499cd893e1f620791ca6ff7107cf270781e587eced \
+    --hash=sha256:cc72bd1009ba0cf63922e28f94d9d83b920aa2bb28f798a31d0691b02fa3c9b3
+    # via astunparse
 widgetsnbextension==4.0.15 \
     --hash=sha256:8156704e4346a571d9ce73b84bee86a29906c9abfd7223b7228a28899ccf3366 \
     --hash=sha256:de8610639996f1567952d763a5a41af8af37f2575a41f9852a38f947eb82a3b9
     # via ipywidgets
+win32-setctime==1.2.0 ; sys_platform == 'win32' \
+    --hash=sha256:95d644c4e708aba81dc3704a116d8cbc974d70b3bdb8be1d150e36be6e9d1390 \
+    --hash=sha256:ae1fdf948f5640aae05c511ade119313fb6a30d7eabe25fef9764dca5873c4c0
+    # via loguru
 wrapt==2.3.0 \
     --hash=sha256:0a45ffae742ce91a16e11cb6c7cd71e7f9994f3cbd283b962ab093f5c6dcf525 \
     --hash=sha256:0d3fb71e65b001adfc42684522eeccd9c21d8ba679945abc993439567b66e59f \
@@ -3399,6 +3909,12 @@ wrapt==2.3.0 \
     # via
     #   aiobotocore
     #   deprecated
+    #   formulaic
+    #   tensorflow
+x-transformers==2.25.4 \
+    --hash=sha256:550872f0fbe089d83f45b1eb9b9d5304102369c77ce04a07559d88dd9b1b2832 \
+    --hash=sha256:d4e71a9938369851d88e22fa462d5c3545a0dee9f606fa330017e0836c3d0eb7
+    # via fuse-med-ml
 xarray==2026.7.0 \
     --hash=sha256:361b495928fdbf5b58d0969bb6775339019da5e93ca74d61ddf4eb5edd6ce604 \
     --hash=sha256:bf9dd130b93806dc78e90c1b7ac24851b31557b888674c53622235691cf21824
diff --git a/requirements-product.txt b/requirements-product.txt
index 411833e..31b7453 100644
--- a/requirements-product.txt
+++ b/requirements-product.txt
@@ -1630,9 +1630,7 @@ nvidia-cuda-nvrtc==13.3.33 ; sys_platform == 'darwin' \
     --hash=sha256:7b05ecda494c6dabc44231a608b060a71008a730d9dfda932cc508e6d29159e0 \
     --hash=sha256:7d2af818851c0c224d5f92221e9226e51ee23c236df4b51f9194563979c888be \
     --hash=sha256:82530788b8c6164a54d3fd9ae8bcca8893d397c4aeb998861982a03bbe41e204
-    # via
-    #   humming-kernels
-    #   nvidia-cublas
+    # via humming-kernels
 nvidia-cuda-runtime==13.0.96 ; sys_platform != 'darwin' \
     --hash=sha256:7f82250d7782aa23b6cfe765ecc7db554bd3c2870c43f3d1821f1d18aebf0548 \
     --hash=sha256:ef9bcbe90493a2b9d810e43d249adb3d02e98dd30200d86607d8d02687c43f55 \
diff --git a/ruff.toml b/ruff.toml
index ed1c3de..5c0ddfc 100644
--- a/ruff.toml
+++ b/ruff.toml
@@ -1,34 +1,33 @@
 # Exclude a variety of commonly ignored directories.
 exclude = [
-    ".bzr",
-    ".direnv",
-    ".eggs",
-    ".git",
-    ".git-rewrite",
-    ".hg",
-    ".ipynb_checkpoints",
-    ".mypy_cache",
-    ".nox",
-    ".pants.d",
-    ".pyenv",
-    ".pytest_cache",
-    ".pytype",
-    ".ruff_cache",
-    ".svn",
-    ".tox",
-    ".venv",
-    ".vscode",
-    "__pypackages__",
-    "_build",
-    "buck-out",
-    "build",
-    "dist",
-    "node_modules",
-    "site-packages",
-    "venv",
+  ".bzr",
+  ".direnv",
+  ".eggs",
+  ".git",
+  ".git-rewrite",
+  ".hg",
+  ".ipynb_checkpoints",
+  ".mypy_cache",
+  ".nox",
+  ".pants.d",
+  ".pyenv",
+  ".pytest_cache",
+  ".pytype",
+  ".ruff_cache",
+  ".svn",
+  ".tox",
+  ".venv",
+  ".vscode",
+  "__pypackages__",
+  "_build",
+  "buck-out",
+  "build",
+  "dist",
+  "node_modules",
+  "site-packages",
+  "venv",
 ]
 
-
 # Assume Python 3.10
 target-version = "py310"
 
@@ -37,32 +36,32 @@ target-version = "py310"
 # Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or
 # McCabe complexity (`C901`) by default.
 select = [
-    # "D",
-    "E",     # pycodestyle errors
-    "F",     # Pyflakes
-    "FA",    # flake8-future-annotations
-    "FAST",  # FastAPI
-    "FLY",   # flynt
-    "FURB",  # refurb
-    "I",     # isort
-    "ICN",   # flake8-import-conventions
-    "INT",   # flake8-gettext
-    "ISC",   # flake8-implicit-str-concat
-    "NPY",   # NumPy-specific rules
-    "PERF",  # Perflint
-    "PGH",   # pygrep-hooks
-    "PIE",   # flake8-pie
-    "PT",    # flake8-pytest-style
-    "RUF",   # Ruff-specific rules
-    "S",     # flake8-bandit
-    "S608",  # SQL injection
-    "SIM",   # flake8-simplify
-    "SLOT",  # flake8-slots
-    "T10",   # flake8-debugger
-    "TID",   # flake8-tidy-imports
-    "UP",    # pyupgrade
-    "W",     # pycodestyle warnings
-    "YTT",   # flake8-2020
+  # "D",
+  "E",  # pycodestyle errors
+  "F",  # Pyflakes
+  "FA",  # flake8-future-annotations
+  "FAST",  # FastAPI
+  "FLY",  # flynt
+  "FURB",  # refurb
+  "I",  # isort
+  "ICN",  # flake8-import-conventions
+  "INT",  # flake8-gettext
+  "ISC",  # flake8-implicit-str-concat
+  "NPY",  # NumPy-specific rules
+  "PERF",  # Perflint
+  "PGH",  # pygrep-hooks
+  "PIE",  # flake8-pie
+  "PT",  # flake8-pytest-style
+  "RUF",  # Ruff-specific rules
+  "S",  # flake8-bandit
+  "S608",  # SQL injection
+  "SIM",  # flake8-simplify
+  "SLOT",  # flake8-slots
+  "T10",  # flake8-debugger
+  "TID",  # flake8-tidy-imports
+  "UP",  # pyupgrade
+  "W",  # pycodestyle warnings
+  "YTT",  # flake8-2020
 ]
 
 # E501 - line too long (https://docs.astral.sh/ruff/rules/line-too-long/)
diff --git a/uv.lock b/uv.lock
index a8df965..d9181d7 100644
--- a/uv.lock
+++ b/uv.lock
@@ -271,6 +271,7 @@ source = { editable = "." }
 
 [package.optional-dependencies]
 candidate = [
+    { name = "biomed-multi-alignment", extra = ["vllm"], marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "bmfm-targets", extra = ["vllm"], marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "opencv-python-headless" },
     { name = "terrakit" },
@@ -285,6 +286,7 @@ cli = [
     { name = "typer" },
 ]
 ecosystem = [
+    { name = "biomed-multi-alignment" },
     { name = "bmfm-targets" },
     { name = "gridfm-graphkit" },
     { name = "terrakit" },
@@ -314,6 +316,8 @@ test = [
 [package.metadata]
 requires-dist = [
     { name = "ado-core", marker = "extra == 'cli'", specifier = ">=2.0" },
+    { name = "biomed-multi-alignment", marker = "extra == 'ecosystem'", git = "https://github.com/BiomedSciAI/biomed-multi-alignment?rev=0.2.5" },
+    { name = "biomed-multi-alignment", extras = ["vllm"], marker = "extra == 'candidate'", git = "https://github.com/BiomedSciAI/biomed-multi-alignment?rev=0.2.5" },
     { name = "bmfm-targets", marker = "extra == 'ecosystem'", git = "https://github.com/BiomedSciAI/biomed-multi-omic.git" },
     { name = "bmfm-targets", extras = ["vllm"], marker = "extra == 'candidate'", git = "https://github.com/BiomedSciAI/biomed-multi-omic.git" },
     { name = "gridfm-graphkit", marker = "extra == 'ecosystem'", specifier = "==0.8.1" },
@@ -360,7 +364,7 @@ resolution-markers = [
 ]
 dependencies = [
     { name = "array-api-compat", marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
-    { name = "h5py", marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
+    { name = "h5py", version = "3.14.0", source = { registry = "https://pypi.org/simple" }, marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "natsort", marker = "extra == 'extra-15-algorithm-nexus-candidate' or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.13' and extra == 'extra-15-algorithm-nexus-candidate') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.13' and extra == 'extra-15-algorithm-nexus-candidate') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
@@ -385,7 +389,7 @@ resolution-markers = [
 ]
 dependencies = [
     { name = "array-api-compat", marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
-    { name = "h5py", marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
+    { name = "h5py", version = "3.14.0", source = { registry = "https://pypi.org/simple" }, marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "legacy-api-wrap", marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "natsort", marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
     { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "extra == 'extra-15-algorithm-nexus-ecosystem' or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product')" },
@@ -516,6 +520,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d4/2b/04b8a15f3a1c77bc79ddf5c73875327f34b4fa75982df2b76e45e402d364/asttokens-3.0.2-py3-none-any.whl", hash = "sha256:9da13157f5b28becde0bd374fc677dcd3c290614264eff096f167c469cd9f933", size = 28702, upload-time = "2026-07-12T03:31:47.542Z" },
 ]
 
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "six" },
+    { name = "wheel" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f3/af/4182184d3c338792894f34a62672919db7ca008c89abee9b564dd34d8029/astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872", size = 18290, upload-time = "2019-12-22T18:12:13.129Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/2b/03/13dde6512ad7b4557eb792fbcf0c653af6076b81e5941d36ec61f7ce6028/astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8", size = 12732, upload-time = "2019-12-22T18:12:11.297Z" },
+]
+
 [[package]]
 name = "attrs"
 version = "26.1.0"
@@ -525,6 +542,82 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl", hash = "sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309", size = 67548, upload-time = "2026-03-19T14:22:23.645Z" },
 ]
 
+[[package]]
+name = "autograd"
+version = "1.9.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.13' and extra == 'extra-15-algorithm-nexus-candidate') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
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@@ -8839,14 +9600,14 @@ name = "xgrammar"
 version = "0.2.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "apache-tvm-ffi" },
-    { name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.13' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version < '3.13' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
-    { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.13' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version >= '3.13' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
-    { name = "pydantic" },
-    { name = "torch" },
-    { name = "transformers" },
+    { name = "apache-tvm-ffi", marker = "platform_machine != 'ARM64' or sys_platform != 'win32'" },
+    { name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version < '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-product') or (python_full_version < '3.13' and sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version < '3.13' and sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
+    { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version >= '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-product') or (python_full_version < '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (python_full_version < '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (python_full_version < '3.13' and platform_machine != 'ARM64' and extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product') or (python_full_version >= '3.13' and sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-candidate') or (python_full_version >= '3.13' and sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-product') or (platform_machine == 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (platform_machine == 'ARM64' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (platform_machine == 'ARM64' and extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product') or (sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-ecosystem') or (sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-candidate' and extra == 'extra-15-algorithm-nexus-product') or (sys_platform != 'win32' and extra == 'extra-15-algorithm-nexus-ecosystem' and extra == 'extra-15-algorithm-nexus-product')" },
+    { name = "pydantic", marker = "platform_machine != 'ARM64' or sys_platform != 'win32'" },
+    { name = "torch", marker = "platform_machine != 'ARM64' or sys_platform != 'win32'" },
+    { name = "transformers", marker = "platform_machine != 'ARM64' or sys_platform != 'win32'" },
     { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "typing-extensions" },
+    { name = "typing-extensions", marker = "platform_machine != 'ARM64' or sys_platform != 'win32'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/81/f4/e71693d8cec60b7e36dab660784ecc5a6aa51e478a83b556011645c58c87/xgrammar-0.2.3.tar.gz", hash = "sha256:f76423630ae3ac4e090cb38ce1e30e7bcc69b3dee4d22d94353944386a4c6f18", size = 2447704, upload-time = "2026-06-27T04:45:24.759Z" }
 wheels = [