A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
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Updated
Jun 10, 2024 - Jupyter Notebook
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"
This repository has been integrated in https://github.com/DeepRank/deeprank2
Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.
[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding
We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
Methods for the parallel and distributed analysis and mining of the Protein Data Bank using MMTF and Apache Spark.
Structural Bioinformatics Training Workshop & Hackathon 2018
Dataset and utilities for working with protein-protein interactions in 3D
Cancer-dedicated gene set interpretation
An ultra-high-performance protein-protein docking for heterogeneous supercomputers
Contact map analysis for biomolecules; based on MDTraj
Code for Pre-training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction (https://arxiv.org/abs/2301.12068)
Methods for mapping genomic data onto 3D protein structure.
DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data, IEEE BigData 2022
Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model (NeurIPS 2023 Poster)
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