hosseinshn / VelodromeLinks
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
☆17Updated 3 years ago
Alternatives and similar repositories for Velodrome
Users that are interested in Velodrome are comparing it to the libraries listed below
Sorting:
- Models and datasets for perturbational single-cell omics☆153Updated 2 years ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆118Updated 5 months ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆49Updated 5 months ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆34Updated last week
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆156Updated 3 years ago
- Multi-omics integration method using AE and GCN☆36Updated 2 years ago
- A visible neural network model for drug response prediction☆144Updated last year
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆102Updated 11 months ago
- Few shot learning for cancer☆36Updated 3 years ago
- UCE is a zero-shot foundation model for single-cell gene expression data☆208Updated 4 months ago
- BRAID is a department within Genentech dedicated to advancing biological and clinical sciences through artificial intelligence.☆202Updated 3 weeks ago
- Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data☆120Updated last month
- Assorted tools for interacting with .gct, .gctx files and other Connectivity Map (Broad Institute) data/tools☆130Updated 2 years ago
- Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.☆71Updated last month
- Framework for Interpretable Neural Networks☆106Updated 3 months ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆50Updated 3 years ago
- ☆80Updated 11 months ago
- Images and other data from the JUMP Cell Painting Consortium☆174Updated 2 weeks ago
- ☆70Updated last month
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆129Updated 4 months ago
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆81Updated 8 months ago
- ☆67Updated last year
- Deep Learning the T Cell Receptor Binding Specificity of Neoantigen☆82Updated 3 years ago
- Contextual AI models for single-cell protein biology☆86Updated 5 months ago
- ☆34Updated 2 months ago
- Python packaging for CPTAC data☆96Updated last year
- A Deep Learning based Efficacy Prediction System for drug discovery☆67Updated 2 years ago
- ☆72Updated 10 months ago
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 2 years ago
- ☆52Updated 7 months ago