OmicsML/dance
DANCE: a deep learning library and benchmark platform for single-cell analysis
This project helps biological researchers and computational biologists systematically analyze single-cell gene expression data. It takes raw single-cell data, applies advanced deep learning methods, and produces insights such as identified cell types, cell clusters, or spatial domains. Scientists studying cellular biology, disease mechanisms, or drug discovery would use this.
384 stars.
Use this if you need to reliably preprocess and analyze complex single-cell omics data, moving beyond manual trial-and-error to data-driven and automated workflows for tasks like cell type annotation or spatial domain identification.
Not ideal if you are not working with single-cell data or if your primary need is general-purpose deep learning model development outside of omics.
Stars
384
Forks
36
Language
Python
License
BSD-2-Clause
Category
Last pushed
Mar 02, 2026
Commits (30d)
0
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