Software for predicting translation initiation rates in bacteria

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

DELEAT is a bioinformatic analysis pipeline for the design of large-scale genome deletions in bacterial genomes.

An interpretable deep learning-based cell line-specific essential protein predictior

Deep neural network based prediction model for gene essentiality prediction in microbes

Biological foundation modeling from molecular to genome scale

AlphaFold 3 inference pipeline.

Synthetic promoter design in Escherichia coli based on multinomial diffusion model

Synthetic promoter design in Escherichia coli based on multinomial diffusion model

Code for the tutorial/review paper for RL-based-fine-tuniing. In this code, we especially focus on the design of biological sequences like DNA (enhancers) and RNA (UTRs) design.

An educational resource to help anyone learn deep reinforcement learning.

METIS: A versatile active learning workflow for optimization of genetic and metabolic networks

Deep Reinforcement Learning for de-novo Drug Design

Code for "Gene-Gene Interaction Detection with Deep Learning"

The code for paper "Synthetic Promoter Design in Escherichia coli based on Deep Genera-tive Network"

Code and data for promoter evolution model CAPE. Please use our website http://www.cape-promoter.com or http://47.101.71.81 for directed evolution for your sequences.

Generating and scoring novel enzyme sequences with a variety of models and metrics

Machine learning prediction of enzyme optimum pH

Neural Collaborative Filtering

CLEAN: a contrastive learning model for high-quality functional prediction of proteins

Predicting Corynebacterium glutamicum Promoters Based on Novel Feature Descriptors and Feature Selection Techniques

This repository contains implementations and illustrative code to accompany DeepMind publications

Implementation of Alpha Fold 3 from the paper: "Accurate structure prediction of biomolecular interactions with AlphaFold3" in PyTorch

https://www.nature.com/articles/s41598-020-74091-z#Tab1

Machine-learning-based general bacterial promoter prediction tool.

GPro: a toolbox for Generative approaches in promoter design