scGNN
importedsoftware/scgnn
scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/juexinwang/scGNN
- Documentation
- unknown
- Tags
- graph-neural-network · scrna-seq-analysis · 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.
- scDeepSortgraph-neural-network · single-cell
Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network
- scarfscrna-seq-analysis · single-cell
Memory-efficient single-cell analysis in Python. Stream RNA, ATAC, CITE-seq and multi-omics from local or remote Zarr stores, from laptop to atlas scale, with reusable fingerprinted results.
- scClustVizscrna-seq-analysis · single-cell
Explore and share your scRNAseq clustering results
- scAlignscrna-seq-analysis · single-cell
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches
- GNNs-For-Chemistsgraph-neural-network
Implementations of different GNNs from scratch for chemists
- SCPscrna-seq-analysis
An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.
- api.github.com/repos/juexinwang/scGNNretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-07-25, 154 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/40.json→ .entries["scgnn"]
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