dance
importedsoftware/dance
DANCE: a deep learning library and benchmark platform for single-cell analysis
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- BSD-2-Clause(osi)
- Status
- active
- Maturity
- deployed
- Organization
- OmicsML
- Country
- unknown
- Homepage
- pydance.readthedocs.io
- Repository
- github.com/OmicsML/dance
- Documentation
- unknown
- Tags
- benchmark · bioinformatics · computational-biology · dance · data-science · deep-learning · graph-neural-networks · machine-learning
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- seurigiotto-benchmark-frameworkbenchmark · bioinformatics · computational-biology
Optimized pipelines for Spatial Transcriptomics (ST) data analysis using Seurat & Giotto, designed for reproducible benchmarking and biological insight.
- grapheinbioinformatics · computational-biology · graph-neural-networks
Protein Graph Library
- molgraphbioinformatics · computational-biology · graph-neural-networks
Graph neural networks for molecular machine learning: Implemented and compatible with TensorFlow and Keras.
- SLATbioinformatics · graph-neural-networks
Spatial-Linked Alignment Tool
- NanoVarBenchbenchmark · bioinformatics
Evaluating Nanopore-based bacterial variant calling
- FlowMolcomputational-biology · graph-neural-networks
Mixed continous/categorical flow-matching model for de novo molecule generation.
- api.github.com/repos/OmicsML/danceretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-07-24, 389 stars, license reported as BSD-2-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/28.json→ .entries["dance"]
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