ttgump / scDCC

Related projects ⓘ

Alternatives and complementary repositories for scDCC

• ciortanmadalina / contrastive-sc
  ☆14Updated 3 years ago
• ttgump / scDeepCluster_pytorch
  Pytorch implementation of scDeepCluster for Single Cell RNA-seq data
  ☆30Updated 4 months ago
• ttgump / scDeepCluster
  scDeepCluster for Single Cell RNA-seq data
  ☆99Updated 4 months ago
• xuebaliang / scziDesk
  Deep soft K-means clustering with self-training for single cell RNA sequence data
  ☆22Updated 4 years ago
• xiaoyeye / CCST
  Cell clustering for spatial transcriptomics data with graph neural network
  ☆58Updated last year
• QUST-AIBBDRC / scGMAI
  scGMAI: a Gaussian mixture model for clustering single-cell RNA-seq data based on deep autoencoder
  ☆15Updated 3 years ago
• jianhuupenn / ItClust
  Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis
  ☆52Updated 2 years ago
• hui2000ji / scETM
  A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.
  ☆48Updated 2 years ago
• zpliulab / GENELink
  ☆26Updated 2 years ago
• kodaim1115 / scMM
  ☆16Updated 3 years ago
• kimmo1019 / scDEC
  Simultaneous deep generative modeling and clustering of single cell genomic data
  ☆29Updated 2 years ago
• davidbuterez / CellVGAE
  An unsupervised scRNA-seq analysis workflow with graph attention networks
  ☆24Updated last year
• OSU-BMBL / deepmaps
  Single-cell biological network inference using a heterogeneous graph transformer
  ☆67Updated last year
• caokai1073 / uniPort
  a unified single-cell data integration framework by optimal transport
  ☆31Updated last month
• XLearning-SCU / scBridge
  ☆16Updated 3 months ago
• Su-informatics-lab / DSTG
  Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence
  ☆34Updated 2 years ago
• tabdelaal / SpaGE
  Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data
  ☆28Updated 4 months ago
• openproblems-bio / neurips2021-notebooks
  ☆28Updated 2 years ago
• YangLabHKUST / Portal
  Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets
  ☆31Updated last year
• zcang / SpaOTsc
  ☆44Updated last year
• wukevin / babel
  Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
  ☆39Updated last year
• melobio / Concerto-reproducibility
  ☆36Updated last year
• ciortanmadalina / graph-sc
  ☆17Updated 2 years ago
• xuyungang / scIGANs
  Generative adversarial networks for single-cell RNA-seq imputation
  ☆36Updated 4 years ago
• OSU-BMBL / scDEAL
  Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data
  ☆48Updated 4 months ago
• JinmiaoChenLab / GraphST
  ☆91Updated 8 months ago
• QIFEIDKN / STAGATE
  Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
  ☆38Updated last year
• cmzuo11 / scMVAE
  Deep joint-leaning single-cell multi-omics model
  ☆16Updated 2 years ago
• txWang / BERMUDA
  BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.
  ☆27Updated 4 years ago
• YangLabHKUST / SpatialScope
  A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models
  ☆53Updated 5 months ago