sbm-tools is a simple python package for creating, modifying, and maintaining input files for native Structure-Based Model simulations to be used with the popular simulation software GROMACS.
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Updated
Mar 11, 2020 - Python
sbm-tools is a simple python package for creating, modifying, and maintaining input files for native Structure-Based Model simulations to be used with the popular simulation software GROMACS.
Python library for implementing geometrical representations of curves.
Protein folding is the physical process by which a protein chain attains its functional three-dimensional structure from a simple sequence of amino acids.
Your open-source alternative to AlphaFold3🚀
Hybridized distance- and contact-based hierarchical protein folding
Lightning-Fast Template-free Protein Folding based on Predicted Residue Contacts and Secondary Structure
CA-2-HCOMB is a tool for simplifying single-chain protein structures from PDB files into manageable models like various honeycombs, retaining essential information for in-depth computations. It's efficient for large datasets and machine learning, and user-friendly for research and education.
The largest open-source dataset for Protein Single Sequence Secondary Structure prediction.
"Train Your Reinforcement Learning Algorithm To This Protein Folding Problem Simulation". This is part of my bachelor thesis. The latest version of this env is in the LogDQN_ProteinHP repository.
The working repository for my bachelor thesis with title : "LOGDQN DEEP REINFORCEMENT LEARNING IMPLEMENTATION FOR SOLVING HYDROPHOBIC-POLAR MODEL PROTEIN FOLDING PROBLEM (Tendean et al, 2020)"
A streamlit app extending the capabilities of the Jasco spectra manager for fluorescence-spectroscopy protein analytics
Implementation of the HP protein folding model with commands line interface
This is a repo for the "Monte Carlo Simulations of Protein Folding" project. This project is my final project in the computational physics course at Brown University, taken in spring 2018.
A Monte-Carlo Code: Sequential Importance Sampling with Pilot-Exploration Resampling (SISPER) Applied to a 2D Protein Folding
ResNetQA: Improved protein model quality assessment by integrating sequential and pairwise features using deep learning
A package for protein conformational ensemble analyses based on a differential geometry representation of protein backbones.
Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch
a package of Python modules and example scripts for experimenting with the two-dimensional HP lattice model of Dill and Chan.
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