hosseinshn / VelodromeLinks
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
☆17Updated 4 years ago
Alternatives and similar repositories for Velodrome
Users that are interested in Velodrome are comparing it to the libraries listed below
Sorting:
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆165Updated 4 years ago
- ☆67Updated 5 months ago
- Models and datasets for perturbational single-cell omics☆171Updated 3 years ago
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 3 years ago
- ☆66Updated 2 years ago
- Framework for Interpretable Neural Networks☆112Updated 9 months ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆51Updated 4 months ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆135Updated 10 months ago
- ☆88Updated last year
- ☆76Updated last year
- A visible neural network model for drug response prediction☆150Updated 2 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆59Updated 5 months ago
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆90Updated last year
- Python packaging for CPTAC data☆108Updated last year
- ☆48Updated 5 months ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆124Updated last year
- Assorted tools for interacting with .gct, .gctx files and other Connectivity Map (Broad Institute) data/tools☆136Updated 3 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- MOLI: Multi-Omics Late Integration with deep neural networks for drug response prediction☆55Updated 5 years ago
- UCE is a zero-shot foundation model for single-cell gene expression data☆234Updated 10 months ago
- Few shot learning for cancer☆36Updated 4 years ago
- BEELINE: evaluation of algorithms for gene regulatory network inference☆199Updated last month
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆160Updated 3 years ago
- Comprehensive suite for evaluating perturbation prediction models☆113Updated 2 weeks ago
- Contextual AI models for single-cell protein biology☆96Updated 10 months ago
- Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data☆123Updated 3 months ago
- KGWAS: novel genetics discovery enabled by massive functional genomics knowledge graph☆77Updated 9 months ago
- ☆56Updated last year
- Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network☆106Updated 2 years ago
- Clinical sequencing-based primary site classifier☆37Updated last year