jingcheng-du / Gene2vecLinks
Gene2Vec: Distributed Representation of Genes Based on Co-Expression
☆125Updated 3 years ago
Alternatives and similar repositories for Gene2vec
Users that are interested in Gene2vec are comparing it to the libraries listed below
Sorting:
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 2 years ago
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆160Updated 3 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- Comprehensive suite for evaluating perturbation prediction models☆89Updated this week
- Toolbox - generic utilities for data processing (e.g., parsing, proximity, guild scoring, etc...)☆112Updated 3 years ago
- Models and datasets for perturbational single-cell omics☆164Updated 3 years ago
- ☆28Updated 5 years ago
- covolutional neural network based coexpression analysis☆79Updated 5 years ago
- ☆85Updated 2 years ago
- ☆22Updated 11 months ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆124Updated 8 months ago
- Assorted tools for interacting with .gct, .gctx files and other Connectivity Map (Broad Institute) data/tools☆134Updated 3 years ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆51Updated last month
- Code for evaluating single cell foundation models scBERT and scGPT☆46Updated last year
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆151Updated last year
- ☆79Updated last month
- Multi-omics integration method using AE and GCN☆37Updated 2 years ago
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆157Updated 3 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆111Updated last year
- Transformer for One-Stop Interpretable Cell-type Annotation☆145Updated last year
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆84Updated 11 months ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆48Updated 2 months ago
- KGWAS: novel genetics discovery enabled by massive functional genomics knowledge graph☆74Updated 6 months ago
- Single-Cell (Perturbation) Model Library☆73Updated last month
- ☆72Updated last year
- Single-cell biological network inference using a heterogeneous graph transformer☆76Updated 7 months ago
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆34Updated 2 years ago
- A visible neural network model for drug response prediction☆148Updated 2 years ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆148Updated 7 months ago
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆293Updated 8 months ago