schulter / EMOGILinks
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
☆154Updated 3 years ago
Alternatives and similar repositories for EMOGI
Users that are interested in EMOGI are comparing it to the libraries listed below
Sorting:
- Multi-omics integration method using AE and GCN☆36Updated 2 years ago
- MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in…☆167Updated 4 years ago
- Toolbox - generic utilities for data processing (e.g., parsing, proximity, guild scoring, etc...)☆111Updated 3 years ago
- Gene2Vec: Distributed Representation of Genes Based on Co-Expression☆122Updated 3 years ago
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆156Updated 3 years ago
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆149Updated last year
- Contextual AI models for single-cell protein biology☆88Updated 5 months ago
- A visible neural network model for drug response prediction☆147Updated last year
- Deep-Learning framework for multi-omic and survival data integration☆82Updated last year
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 2 years ago
- A VGAE-based model to infer transcription factor regulatory network☆27Updated 3 years ago
- Assorted tools for interacting with .gct, .gctx files and other Connectivity Map (Broad Institute) data/tools☆132Updated 3 years ago
- ☆23Updated 4 years ago
- MOLI: Multi-Omics Late Integration with deep neural networks for drug response prediction☆55Updated 4 years ago
- CNN architecture for predicting DNA binding sites for Transcription Factors☆53Updated 6 years ago
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆34Updated 2 years ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆121Updated 6 months ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆81Updated 9 months ago
- Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network☆86Updated 2 years ago
- ☆84Updated 2 years ago
- [NBME] Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning☆21Updated 4 months ago
- Cell clustering for spatial transcriptomics data with graph neural network☆63Updated 2 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆50Updated 3 years ago
- ☆9Updated 5 years ago
- ☆42Updated 8 months ago
- ☆47Updated last month
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- Multi-omics biomarker discovery tool exploiting a gene-gene interaction network☆16Updated last year
- Framework for Interpretable Neural Networks☆108Updated 4 months ago