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http://dbpedia.org/ontology/abstract The Kabsch algorithm, named after , is a mThe Kabsch algorithm, named after , is a method for calculating the optimal rotation matrix that minimizes the RMSD (root mean squared deviation) between two paired sets of points. It is useful in graphics, cheminformatics to compare molecular structures, and also bioinformatics for comparing protein structures (in particular, see root-mean-square deviation (bioinformatics)). The algorithm only computes the rotation matrix, but it also requires the computation of a translation vector. When both the translation and rotation are actually performed, the algorithm is sometimes called partial Procrustes superimposition (see also orthogonal Procrustes problem). (see also orthogonal Procrustes problem).
http://dbpedia.org/ontology/wikiPageExternalLink https://www.pymolwiki.org/index.php/Kabsch + , http://www.mathworks.com/matlabcentral/fileexchange/25746-kabsch-algorithm + , https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.transform.Rotation.align_vectors.html + , http://cnx.org/content/m11608/latest/ + , https://wiki.pymol.org/index.php/Cealign + , https://github.com/oleg-alexandrov/projects/blob/master/eigen/Kabsch.cpp + , https://github.com/charnley/rmsd. +
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rdfs:comment The Kabsch algorithm, named after , is a mThe Kabsch algorithm, named after , is a method for calculating the optimal rotation matrix that minimizes the RMSD (root mean squared deviation) between two paired sets of points. It is useful in graphics, cheminformatics to compare molecular structures, and also bioinformatics for comparing protein structures (in particular, see root-mean-square deviation (bioinformatics)).t-mean-square deviation (bioinformatics)).
rdfs:label Kabsch algorithm
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