Python Protein Resources

Molecular Docking integrated in Jupyter Notebooks Description | Citation | Installation | Examples | Limitations | License Table of content Descriptio

RITA: a Study on Scaling Up Generative Protein Sequence Models RITA is a family of autoregressive protein models, developed by a collaboration of Ligh

Protein GLM (wip) Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capabil

GVP Transformer (wip) Implementation of the GVP-Transformer, which was used in the paper Learning inverse folding from millions of predicted structure

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

Molecular Nodes 🧬 🔬 💻 Buy Me a Coffee to Keep Development Going! Join a Community of Blender SciVis People! What is Molecular Nodes? Molecular Node

Description: ProtFeat is designed to extract the protein features by employing POSSUM and iFeature python-based tools. ProtFeat includes a total of 39

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

B4PPI Benchmarking Pipeline for the Prediction of Protein-Protein Interactions How this benchmarking pipeline has been built, and how to use it, is de

polyprotein_stats A small tool to test and visualize protein embeddings and amino acid proportions. Currently deployed on streamlit.io. Given a set of

Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022) Please cite "Independent SE(3)-Equivar

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

OntoProtein This is the implement of the paper "OntoProtein: Protein Pretraining With Ontology Embedding". OntoProtein is an effective method that mak

ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In

PROTEIN-EXPRESSION-ANALYSIS-FOR-DOWN-SYNDROME Down syndrome (DS) is a chromosomal disorder where organisms have an extra chromosome 21, sometimes know

RFDesign: Protein hallucination and inpainting with RoseTTAFold Jue Wang (juewan

Are you tired of using visualization software, or full blown suites just to separate protein chains / ligands ? Are you tired of organizing the mess o

This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

AWS RoseTTAFold Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch. Overview Proteins are large biomolecules that play

Uni-Fold: Training your own deep protein-folding models. This package provides and implementation of a trainable, Transformer-based deep protein foldi

Uni-Fold: Training your own deep protein-folding models. This package provides an implementation of a trainable, Transformer-based deep protein foldin

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks Requirements python 0.10+ rdkit 2020.03.3.0 biopython 1.78 openbabel 2.4

PRIP PRIP：A Protein-RNA Interface Predictor Based on Semantics of Sequences installation gensim==3.8.3 matplotlib==3.1.3 xgboost==1.3.3 prettytable==2

trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

This package is a python library with tools for the Molecular Simulation - Software Gromos. It allows you to easily set up, manage and analyze simulations in python.

Introduction orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner. Other popular ORF searching tools

Explore RNA-Protein interactions. RNPFind is a bioinformatics tool. It takes an RNA transcript as input and gives a list of RNA binding protein (RBP)

What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio

peptides.py Physicochemical properties and indices for amino-acid sequences. 🗺️ Overview peptides.py is a pure-Python package to compute common descr

A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features

A geometric deep learning pipeline for predicting protein interface contacts.

RGN2-Replica (WIP) To eventually become an unofficial working Pytorch implementation of RGN2, an state of the art model for MSA-less Protein Folding f

Using a predicted aligned error matrix corresponding to an AlphaFold2 model , returns a series of lists of residue indices, where each list corresponds to a set of residues clustering together into a pseudo-rigid domain.

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

Invariant Point Attention - Pytorch Implementation of Invariant Point Attention as a standalone module, which was used in the structure module of Alph

ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily

kaggle-hpa-2021-7th-place-solution Code for 7th place solution of Human Protein Atlas - Single Cell Classification on Kaggle. A description of the met

Denoising Diffusion Probabilistic Model for Proteins Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to gen

[TensorFlow] Protein Interface Prediction using Graph Convolutional Networks Unofficial TensorFlow implementation of Protein Interface Prediction usin

ProteinLM We pretrain protein language model based on Megatron-LM framework, and then evaluate the pretrained model results on TAPE (Tasks Assessing P

ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc

ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc

ProteinBERT is a universal protein language model pretrained on ~106M proteins from the UniRef90 dataset. Through its Python API, the pretrained model can be fine-tuned on any protein-related task in a matter of minutes. Based on our experiments with a wide range of benchmarks, ProteinBERT usually achieves state-of-the-art performance. ProteinBERT is built on TenforFlow/Keras.

DeepFRI Deep functional residue identification Citing @article {Gligorijevic2019, author = {Gligorijevic, Vladimir and Renfrew, P. Douglas and Koscio

Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay

Structural basis for solubility in protein expression systems Large-scale protein production for biotechnology and biopharmaceutical applications rely

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and

trRosetta - Pytorch (wip) Implementation of trRosetta and trDesign for Pytorch, made into a convenient package

Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom