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The Wayback Machine - https://web.archive.org/web/20200903100443/https://github.com/topics/rmsd
Here are
19 public repositories
matching this topic...
An open library for the analysis of molecular dynamics trajectories
Calculate Root-mean-square deviation (RMSD) of two molecules, using rotation, in xyz or pdb format
Updated
Jul 27, 2020
Python
Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure
Updated
Aug 11, 2020
Python
register 3-D point clouds using rotation, translation, and scale transformations.
Updated
Jul 10, 2020
Python
Python script that receives a molecular dynamics or Monte Carlo trajectory and performs agglomerative clustering to classify similar structures.
Updated
Nov 7, 2019
Python
header-only C++ library for registering 3-D point clouds using rotation, translation, and scale transformations
A protein fragments picker
Updated
Sep 26, 2019
OCaml
PCA and normal mode analysis of proteins
Updated
Feb 3, 2020
Python
MODE-TASK plugin for PyMOL
Updated
Mar 18, 2019
Python
open toolbox for structural comparison, a fork aiming a deployment without PyInstaller under Linux. Note the project «aRMSD-minimalWindowsSupport», too.
Updated
Dec 13, 2018
Python
Calculate and apply the optimal transformation matrix that minimizes the RMSD (root mean squared deviation) between two paired sets of points.
Updated
Mar 13, 2019
JavaScript
Command line recipes for the working chemoinformatician
Fortran code of Quaternion Characteristic Polynomial (QCP) superposition method
Updated
Apr 26, 2017
Fortran
F@H Data Analysis: Root-mean-square Deviation & Radius of Gyration Calculations
Updated
Nov 10, 2017
Perl
aligns arbitrarily ordered isomers
Updated
Dec 28, 2019
Python
Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats.
Updated
Jul 6, 2020
Julia
Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats, using Pymol as a module
Updated
Jul 6, 2020
Python
Updated
Mar 28, 2019
Python
Clustering for molecular configurations
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