Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

Deep learning for gene expression inference

A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

Fast visualization tool for large-scale and high dimensional single-cell data

Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016

A COBRApy extension for genome-scale models of metabolism and expression (ME-models)

Single cell Nanopore sequencing data for Genotype and Phenotype

The official code implementation for Chromoformer in PyTorch. (Lee et al., Nature Communications. 2022)

This repository contains the tensorflow implementation of "GNE: A deep learning framework for gene network inference by aggregating biological information"

Transcripts annotation and GO enrichment Fisher tests

GEDFN: Graph-Embedded Deep Feedforward Network

scripts for RNA-Seq analysis

RNA-seq pipeline for raw sequence alignment and transcript/gene quantification.

Variational Auto-Encoder that generates synthetic gene expression data

Survival Prediction for Gastric Cancer via Multimodal Learning of Whole Slide Images and Gene Expression -- BIBM 2022

Predictive models and analysis of cancer prognosis and drug response using primary tumor microbial abundances derived from WGS and RNA-seq sequencing data for 32 TCGA cancers (Poore et al. Nature 2020), including equivalent models using TCGA RNA-seq gene expression and combined microbial abundance and gene expression for comparison.

MYB transcription factors are one of the largest gene family in plants and control many processes. This repository provides additional background to the #MYB_Monday tweets

Using Machine Learning to Identify Glioblastoma patients with NF1 inactivation

MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.

A collection of Python modules equivalent to R ReQTL Toolkit aims to identify the association between expressed SNVs with their gene expression using RNA-sequencing data.