Alternatives and similar repositories for EFAAR_benchmarking

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

• carpenter-singh-lab / 2023_Arevalo_NatComm_BatchCorrection
  Evaluating batch correction methods for image-based cell profiling
  ☆14Updated 5 months ago
• theislab / CellFlow
  Modeling complex perturbations with CellFlow
  ☆49Updated this week
• carpenter-singh-lab / 2022_Haghighi_NatureMethods
  High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
  ☆48Updated 4 months ago
• recursionpharma / maes_microscopy
  Official repo for Recursion's accepted spotlight paper at NeurIPS 2023 Generative AI & Biology workshop.
  ☆59Updated 6 months ago
• aaronwtr / PertEval
  Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.
  ☆25Updated 2 months ago
• theislab / prophet
  ☆32Updated last month
• jump-cellpainting / 2024_Chandrasekaran_NatureMethods
  ☆62Updated 3 months ago
• jump-cellpainting / JUMP-Target
  Lists and 384-well plate maps of compounds and genetic perturbations designed to assess connectivity in profiling assays
  ☆21Updated 5 months ago
• carpenter-singh-lab / 2023_Cimini_NatureProtocols
  Optimizing the Cell Painting assay for image-based profiling
  ☆20Updated 5 months ago
• broadinstitute / cellpainting-gallery
  Cell Painting Gallery
  ☆90Updated last week
• jump-cellpainting / datasets
  Images and other data from the JUMP Cell Painting Consortium
  ☆169Updated 3 months ago
• broadinstitute / lincs-cell-painting
  Processed Cell Painting Data for the LINCS Drug Repurposing Project
  ☆28Updated 2 years ago
• theislab / IMPA
  ☆13Updated 4 months ago
• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆32Updated last month
• sanderlab / CellBox
  CellBox: Interpretable Machine Learning for Perturbation Biology
  ☆54Updated last year
• HakimBenkirane / CustOmics
  A deep-learning framework for multi-omics integration
  ☆26Updated last year
• bowang-lab / genomic-FM
  ☆25Updated last month
• microsoft / zero-shot-scfoundation
  ☆64Updated 9 months ago
• Genentech / sVAE
  ☆63Updated last year
• theislab / chemCPA
  Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
  ☆113Updated 3 months ago
• bunnelab / virtues
  A foundation model framework for analyzing multiplexed tissue imaging data across molecular, cellular and tissue scales enabling clinical…
  ☆30Updated 3 months ago
• DeepGraphLearning / scCello
  [NeurIPS 2024 Spotlight] A cell-ontology guided transcriptome foundation model
  ☆15Updated 2 months ago
• uhlerlab / cross-modal-autoencoders
  ☆55Updated 2 years ago
• bowang-lab / scFormer
  ☆19Updated 2 years ago
• theislab / multicpa
  ☆14Updated 2 years ago
• ratschlab / pmvae
  Code for pmVAE model, seen in ICML CompBio '21
  ☆12Updated last year
• Genentech / pascient
  ☆16Updated last month
• Genentech / iterative-perturb-seq
  Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors
  ☆40Updated last year
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆100Updated 9 months ago
• ml-jku / cloome
  ☆38Updated 7 months ago