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

For fine-tuning Enformer using paired WGS & gene expression data

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The full training script for Enformer - Tensorflow Sonnet

Code for improving the performance of sequence-to-expression models for making individual-specific gene expression predictions by fine-tuning them on personal genome and transcriptome data.

Enformer Celltyping is a tensorflow, multi-headed attention based model that incorporates distal effects of Deoxyribonucleic Acid (DNA) interactions to predict histone marks across diverse cell types.

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We provide pytorch training scripts for enformer and borzoi

Forked from https://github.com/deepmind/deepmind-research/

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EnFormer architecture for Polyp-Segmentation

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Implementation of Enformer, attention network for predicting gene expression, in Jax

Code to use the Enformer model to make predictions on new sequences

Repository containing code to extract the embeddings of the Enformer model.

An AI framework for analyzing the link between multi-omics data (SNP, DNA methylation) using classical machine learning models (LDA, HMM) and SOTA AI models (GPT, BERT, Enformer).

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Aiming to create a personalized version of Google's AlphaGenome, using Enformer as a reference for architectural and fine tuning.

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This is an enformer finetune script repository. It mainly finetune enformer on a gene expression level pridiction task and a EPI prediction task.

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Enformer Documentation

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Dataloader for enformer