Alternatives and similar repositories for chemCPA

Users that are interested in chemCPA are comparing it to the libraries listed below

• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆57Updated 4 months ago
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆119Updated last year
• mims-harvard / PINNACLE
  Contextual AI models for single-cell protein biology
  ☆95Updated 9 months ago
• ArcInstitute / cell-eval
  Comprehensive suite for evaluating perturbation prediction models
  ☆110Updated 3 weeks ago
• theislab / CellFlow
  Modeling complex perturbations with CellFlow
  ☆99Updated last week
• aaronwtr / PertEval
  Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.
  ☆31Updated 4 months ago
• theislab / sc-pert
  Models and datasets for perturbational single-cell omics
  ☆168Updated 3 years ago
• Perturbation-Response-Prediction / PRnet
  PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…
  ☆68Updated 11 months ago
• idekerlab / DrugCell
  A visible neural network model for drug response prediction
  ☆149Updated 2 years ago
• dohlee / chromoformer
  The official code implementation for Chromoformer in PyTorch. (Lee et al., Nature Communications. 2022)
  ☆36Updated 2 years ago
• microsoft / zero-shot-scfoundation
  ☆75Updated last year
• yhr91 / GEARS_misc
  ☆24Updated last year
• wukevin / tcr-bert
  Large language modeling applied to T-cell receptor (TCR) sequences.
  ☆57Updated 3 years ago
• const-ae / linear_perturbation_prediction-Paper
  ☆62Updated 4 months ago
• snap-stanford / GEARS
  GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
  ☆315Updated 10 months ago
• bunnech / cellot
  Learning Single-Cell Perturbation Responses using Neural Optimal Transport
  ☆151Updated last year
• xianglin226 / Benchmarking-Single-Cell-Perturbation
  Single-Cell (Perturbation) Model Library
  ☆84Updated 3 months ago
• jump-cellpainting / datasets
  Images and other data from the JUMP Cell Painting Consortium
  ☆178Updated this week
• EperLuo / scDiffusion
  A model developed for the generation of scRNA-seq data
  ☆79Updated 9 months ago
• hui2000ji / scETM
  A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.
  ☆53Updated 3 years ago
• KatarinaYuan / awesome-single-cell-foundation
  Paper collection for single cell foundation models
  ☆35Updated last year
• carpenter-singh-lab / 2022_Haghighi_NatureMethods
  High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
  ☆51Updated 3 months ago
• sanderlab / scPerturb
  scPerturb: A resource and a python/R tool for single-cell perturbation data
  ☆154Updated 9 months ago
• kekegg / DLEPS
  A Deep Learning based Efficacy Prediction System for drug discovery
  ☆73Updated 3 years ago
• altoslabs / perturbench
  ☆65Updated last month
• theislab / nicheformer
  Repository for Nicheformer: a foundation model for single-cell and spatial omics
  ☆127Updated last week
• sanderlab / CellBox
  CellBox: Interpretable Machine Learning for Perturbation Biology
  ☆56Updated 2 years ago
• HantaoShu / DeepSEM
  ☆86Updated 2 years ago
• jkobject / geneformer
  ☆85Updated 3 months ago
• sjgosai / boda2
  Computational Optimization of DNA Activity (CODA)
  ☆65Updated 8 months ago