scDataset
importeddata/scdataset
scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- scDataset
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/scDataset/scDataset
- Documentation
- unknown
- Tags
- big-data · bioinformatics · deep-learning · machine-learning · omics · pytorch · rna-seq · single-cell
- 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.
- biosetsbig-data · omics
A bioinformatics extension of 🤗 Datasets library, built for ML applications on biological and omics data, offering easy integration of metadata and low-code data management tools.
- Phenoversebioinformatics · omics · single-cell
Deep interpretable learning of sample representations for characterizing disease states in single-cell transcriptomics
- ReCoNomics · rna-seq · single-cell
Exploring multicellular coordination from single-cell gene expression / multi-omics using mutlilayer network representations
- ASAPbioinformatics · rna-seq · single-cell
ASAP : Automated Single-cell Analysis Pipeline
- omicversebioinformatics · omics · single-cell
A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.
- scPRINTpytorch · rna-seq · single-cell
single cell foundation model for Gene network inference and more
- api.github.com/repos/scDataset/scDatasetretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-01-30, 51 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/9.json→ .entries["scdataset"]
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