snap-stanford / KGWASLinks
KGWAS: novel genetics discovery enabled by massive functional genomics knowledge graph
☆75Updated 8 months ago
Alternatives and similar repositories for KGWAS
Users that are interested in KGWAS are comparing it to the libraries listed below
Sorting:
- ☆97Updated 2 months ago
- ☆133Updated 8 months ago
- ☆93Updated 3 weeks ago
- ☆62Updated 4 months ago
- Knowledge-primed neural networks☆38Updated 2 years ago
- Comprehensive suite for evaluating perturbation prediction models☆110Updated 3 weeks ago
- Functional Embedding of Gene Signatures☆48Updated last year
- CMap Notebooks for LINCS 2020 Workshop☆48Updated 4 years ago
- Computational Optimization of DNA Activity (CODA)☆65Updated 8 months ago
- repository containing analysis scripts and auxiliary files☆36Updated 5 years ago
- A Deep Learning based Efficacy Prediction System for drug discovery☆73Updated 3 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆119Updated last year
- Code space for 'Evaluation of large language models for discovery of gene set function'☆41Updated 11 months ago
- ☆75Updated last year
- ☆65Updated last month
- Integrate Any Omics: Towards genome-wide data integration for patient stratification☆57Updated 6 months ago
- Utilizing single-cell omics from patients tumor to predict response and resistance.☆71Updated 2 years ago
- What you need to process the Quarterly DepMap-Omics releases from Terra☆125Updated 2 months ago
- ☆85Updated 3 months ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆51Updated 3 months ago
- ☆27Updated 10 months ago
- Diffusion model for gene regulatory network inference.☆23Updated 4 months ago
- Create cell sentences from sequencing data☆23Updated last year
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆131Updated 9 months ago
- Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.☆60Updated last year
- ☆145Updated last year
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆57Updated 4 months ago
- ☆28Updated 7 months ago
- A deep-learning based multi-modal data integration suite that aims to achieve synesis in a flexible manner☆95Updated last month
- ☆14Updated 6 months ago