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

CodonTransformer (1M+ Downloads); The tool for codon optimization, optimizing DNA for protein expression

A framework for state-of-the-art pre-trained bio foundation models on genomics and transcriptomics modalities.

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

Single cell Nanopore sequencing data for Genotype and Phenotype

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

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

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

scripts for RNA-Seq analysis

Transcripts annotation and GO enrichment Fisher tests

Variational Auto-Encoder that generates synthetic gene expression data

GEDFN: Graph-Embedded Deep Feedforward Network

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.

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

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

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.

Using Machine Learning to Identify Glioblastoma patients with NF1 inactivation