GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
☆410Feb 1, 2025Updated last year
Alternatives and similar repositories for GEARS
Users that are interested in GEARS are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆30Oct 14, 2024Updated last year
- Single-cell perturbation effects prediction benchmark☆105Sep 14, 2026Updated last week
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆153Aug 14, 2024Updated 2 years ago
- State is a machine learning model that predicts cellular perturbation response across diverse contexts☆700Jul 24, 2026Updated 2 months ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆188Feb 25, 2025Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- ☆96Jul 18, 2025Updated last year
- ☆431Nov 23, 2025Updated 10 months ago
- Models and datasets for perturbational single-cell omics☆184Aug 19, 2022Updated 4 years ago
- ☆1,636Apr 29, 2026Updated 4 months ago
- ☆74Jan 14, 2026Updated 8 months ago
- Single-cell perturbation analysis☆346Updated this week
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆69Jan 12, 2026Updated 8 months ago
- Arc Virtual Cell Atlas☆601Aug 28, 2026Updated 3 weeks ago
- GenePert: Leveraging GenePT Embeddings for Gene Perturbation Prediction☆23Oct 29, 2024Updated last year
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Comprehensive suite for evaluating perturbation prediction models☆160Jul 27, 2026Updated last month
- Modeling complex perturbations with CellFlow☆159Updated this week
- PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…☆91Dec 13, 2024Updated last year
- A repository for reproducing experiments from the TxPert paper☆51Mar 25, 2026Updated 5 months ago
- Single-Cell (Perturbation) Model Library☆129Jul 27, 2026Updated last month
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆182Oct 31, 2024Updated last year
- ☆324Mar 18, 2024Updated 2 years ago
- This is the alpha version of the CellOracle package☆501Apr 30, 2026Updated 4 months ago
- 🏃 The go-to single-cell Foundation Model☆162Aug 11, 2026Updated last month
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- ☆100Aug 10, 2026Updated last month
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆160Feb 6, 2025Updated last year
- ☆343Aug 16, 2026Updated last month
- pytorch dataloaders for single-cell perturbation data☆54Jul 18, 2026Updated 2 months ago
- Code for reproducing "Exploring genetic interaction manifolds constructed from rich single-cell phenotypes"☆71Jun 6, 2020Updated 6 years ago
- Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)☆18Jun 15, 2025Updated last year
- ☆15Jul 24, 2024Updated 2 years ago
- UCE is a zero-shot foundation model for single-cell gene expression data☆342Jul 8, 2026Updated 2 months ago
- ☆187Jan 30, 2026Updated 7 months ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to repr…☆260Mar 14, 2026Updated 6 months ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell lev…☆186Sep 7, 2023Updated 3 years ago
- Single cell perturbation prediction☆356Dec 5, 2024Updated last year
- ☆364Dec 13, 2023Updated 2 years ago
- scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics☆52Jan 30, 2026Updated 7 months ago
- ☆137Jul 11, 2026Updated 2 months ago
- ☆40Apr 16, 2025Updated last year