snap-stanford / GEARS
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
☆237Updated last month
Alternatives and similar repositories for GEARS:
Users that are interested in GEARS are comparing it to the libraries listed below
- ☆303Updated last week
- ☆241Updated last month
- UCE is a zero-shot foundation model for single-cell gene expression data☆185Updated 2 weeks ago
- Models and datasets for perturbational single-cell omics☆150Updated 2 years ago
- A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to repr…☆178Updated 3 weeks ago
- ☆301Updated last month
- Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.☆64Updated last month
- Repository for Nicheformer: a foundation model for single-cell and spatial omics☆82Updated 2 months ago
- ☆250Updated 11 months ago
- Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.☆78Updated 11 months ago
- Perturbation Analysis in the scverse ecosystem.☆160Updated last week
- ☆291Updated last year
- Graph-linked unified embedding for single-cell multi-omics data integration☆403Updated last year
- Transformer for One-Stop Interpretable Cell-type Annotation☆138Updated last year
- Single-Cell (Perturbation) Model Library☆42Updated last week
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆114Updated 2 weeks ago
- Benchmarking analysis of data integration tools☆337Updated last month
- ☆117Updated 8 months ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆111Updated last month
- BEELINE: evaluation of algorithms for gene regulatory network inference☆181Updated 3 weeks ago
- Reference mapping for single-cell genomics☆355Updated 2 weeks ago
- ☆52Updated last year
- Formalizing and benchmarking open problems in single-cell genomics☆329Updated last month
- Code for evaluating single cell foundation models scBERT and scGPT☆38Updated 6 months ago
- GeneCompass☆70Updated 7 months ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆96Updated 6 months ago
- gReLU is a python library to train, interpret, and apply deep learning models to DNA sequences.☆251Updated this week
- Spatial alignment of single cell transcriptomic data.☆277Updated 9 months ago
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆126Updated 4 months ago