biomed-AI / GraphSCCLinks
single-cell RNA-seq clustering
☆10Updated 5 years ago
Alternatives and similar repositories for GraphSCC
Users that are interested in GraphSCC are comparing it to the libraries listed below
Sorting:
- ☆14Updated 3 years ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆19Updated last year
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆26Updated 2 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- Code for Nature Scientific Reports 2020 paper: "Unsupervised generative and graph neural methods for modelling cell differentiation" by I…☆18Updated 5 years ago
- ☆79Updated 3 years ago
- ☆17Updated 5 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- Imputation of single cell RNA-sequencing data with autoencoder☆16Updated 4 years ago
- Simultaneous deep generative modeling and clustering of single cell genomic data☆32Updated 2 years ago
- The source code and results for different methods on annotating external testing datsets of human and mouse.☆12Updated 4 years ago
- single-cell graph autoencoder☆24Updated 4 years ago
- Learning disentangled representations of single-cell data for high-quality generation☆16Updated last year
- ☆19Updated 3 years ago
- ☆30Updated 3 years ago
- Python Implementation of SIMLR for single-cell visualization and analysis☆24Updated 3 years ago
- scDCC: Single Cell Deep Constrained Clustering☆41Updated last year
- ☆16Updated 3 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated 2 years ago
- ☆15Updated 3 months ago
- ☆18Updated 4 years ago
- SemI-SUpervised generative Autoencoder models for single cell data☆18Updated 4 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆49Updated 3 months ago
- ☆11Updated 4 years ago
- Conditional out-of-distribution prediction☆63Updated last year
- Biological Network Integration using Convolutions☆62Updated last year
- This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to applications of Deep Learning to …☆15Updated last month
- fast hierarchical clustering for large-scale single-cell data☆10Updated 4 years ago
- a variational autoencoder method for clustering single-cell mutation data☆12Updated last year