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af_backprop

aigem_teamheidelberg2017

The AiGEM software suite of Team Heidelberg 2017

alchemy

alphafill

AlphaFill is an algorithm based on sequence and structure similarity that “transplants” missing compounds to the AlphaFold models. By adding the molecular context to the protein structures, the models can be more easily appreciated in terms of function and structure integrity.

alphafold

Open source code for AlphaFold.

amorehead

My GitHub profile header.

awesome-jax

JAX - A curated list of resources https://github.com/google/jax

bioinformatics

:microscope: Path to a free self-taught education in Bioinformatics!

cadee

CADEE: Computer-Aided Directed Evolution of Enzymes

colabdesign

Making Protein Design accessible to all via Google Colab!

colabfold

Making Protein folding accessible to all via Google Colab!

csu_china

Wiki repository for 2021 iDEC Team: CSU_CHINA

csu_china_2020_modeling

This is the iGEM team project model of CSU_CHINA_2020

dcatools

essay_for_molecular_generation

This repo have a tendency to provide the newest paper about molecular generation or evolution, it will also be convenient for everyone to get info about Drug Discovery).

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

machine-learning-for-proteins

Listing of papers about machine learning for proteins.

my_2021_mcm-icm_a_solution

this is a solution program of 2021 MCM/ICM problem A

organic

Objective-Reinforced Generative Adversarial Networks for Inverse-design Chemistry

papers_for_protein_design_using_dl

List of papers about Proteins Design using Deep Learning

parp1_inhibitor_optimizer

This is a model find optimized PARP1 inhibitor based on ORGANIC

peldom

Personal Profile

peplib_generator

The one model for genesis of peptide ligands

pyswarms

A research toolkit for particle swarm optimization in Python

rfdiffusion

Code for running RFdiffusion

rosettafold

This package contains deep learning models and related scripts for RoseTTAFold

transformercpi

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524