There are 17 repositories under structural-biology topic.
Toolbox for molecular animations in Blender, powered by Geometry Nodes.
A comprehensive library for computational molecular biology
A dependency-free cross-platform swiss army knife for PDB files.
An all-atom protein structure dataset for machine learning.
Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm
macromolecular crystallography library and utilities
Official code repository for EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation
Predicting protein structure through sequence modeling
C-library for calculating Solvent Accessible Surface Areas
Python macromolecular parsing (with .pdb/.cif/.mmtf parsing and production)
VSCode Extension for interactively visualising protein structure data in the editor
A Julia package to read, write and manipulate macromolecular structures
A curated list of awesome computational cryo-EM methods.
PENSA - a collection of python methods for exploratory analysis and comparison of biomolecular conformational ensembles.
Scipion is an image processing framework to obtain 3D models of macromolecular complexes using Electron Microscopy (3DEM)
The Biochemical Algorithms Library
The MPI Bioinformatics Toolkit
PyMOL extension to color AlphaFold structures by confidence (pLDDT).
Graph neural network for generating novel amino acid sequences that fold into proteins with predetermined topologies.
This repository includes the slides and the practicals for the course of Structural Bioinformatics of the MBB/QB degrees at the University of Milano, originally inspired by https://github.com/pb3lab/ibm3202
Set of useful HADDOCK utility scripts
A Julia package to view macromolecular structures in the REPL, in a Jupyter notebook/JupyterLab or in Pluto
PACKMAN: PACKing and Motion ANalysis
An open-source deep learning framework for data mining of protein-protein interfaces or single-residue variants.
Pipeline for the automatic detection and segmentation of particles and cellular structures in 3D Cryo-ET data, based on deep learning (convolutional neural networks).
TomoBEAR is a configurable and customizable modular pipeline for streamlined processing of cryo-electron tomographic data for subtomogram averaging.
A curated list of awesome computational cryo-ET methods.
PyMissense creates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.