theislab / chemCPALinks
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
☆142Updated 11 months ago
Alternatives and similar repositories for chemCPA
Users that are interested in chemCPA are comparing it to the libraries listed below
Sorting:
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆61Updated 3 weeks ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆134Updated last year
- Contextual AI models for single-cell protein biology☆96Updated 11 months ago
- Comprehensive suite for evaluating perturbation prediction models☆120Updated 2 weeks ago
- Modeling complex perturbations with CellFlow☆114Updated last week
- ☆69Updated 6 months ago
- PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…☆74Updated last year
- Single-Cell (Perturbation) Model Library☆89Updated 2 weeks ago
- Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.☆35Updated 6 months ago
- Models and datasets for perturbational single-cell omics☆172Updated 3 years ago
- ☆79Updated 3 weeks ago
- Large language modeling applied to T-cell receptor (TCR) sequences.☆59Updated 3 years ago
- ☆25Updated last year
- A model developed for the generation of scRNA-seq data☆84Updated 2 weeks ago
- BulkFormer: A large-scale foundation model for human bulk transcriptomes☆40Updated last month
- ☆92Updated 5 months ago
- A visible neural network model for drug response prediction☆151Updated 2 years ago
- The official code implementation for Chromoformer in PyTorch. (Lee et al., Nature Communications. 2022)☆37Updated 2 years ago
- CellBox: Interpretable Machine Learning for Perturbation Biology☆56Updated 2 years ago
- Single-cell perturbation effects prediction benchmark☆58Updated 3 weeks ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆52Updated 4 years ago
- Repository for Nicheformer: a foundation model for single-cell and spatial omics☆149Updated 2 months ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆164Updated 11 months ago
- ☆90Updated 2 years ago
- Deep Learning the T Cell Receptor Binding Specificity of Neoantigen☆89Updated 3 years ago
- Images and other data from the JUMP Cell Painting Consortium☆181Updated last week
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆156Updated last year
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆331Updated last year
- ☆74Updated last week
- Computational Optimization of DNA Activity (CODA)☆67Updated 10 months ago