{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T05:32:22Z","timestamp":1769837542383,"version":"3.49.0"},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Sampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise; in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons.<\/jats:p>\n               <jats:p>Results: We present here a python library implementing the full SOM analysis workflow. Large SOMs can readily be applied on heavy data sets. Coupled with visualization tools they have very interesting properties. Descriptors for each conformation of a trajectory are calculated and mapped onto a 3D landscape, the U-matrix, reporting the distance between neighboring neurons. To delineate clusters, we developed the flooding algorithm, which hierarchically identifies local basins of the U-matrix from the global minimum to the maximum.<\/jats:p>\n               <jats:p>Availability and implementation: The python implementation of the SOM library is freely available on github: https:\/\/github.com\/bougui505\/SOM.<\/jats:p>\n               <jats:p>Contact: \u00a0michael.nilges@pasteur.fr or guillaume.bouvier@pasteur.fr<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu849","type":"journal-article","created":{"date-parts":[[2014,12,28]],"date-time":"2014-12-28T01:07:50Z","timestamp":1419728870000},"page":"1490-1492","source":"Crossref","is-referenced-by-count":33,"title":["An automatic tool to analyze and cluster macromolecular conformations based on self-organizing maps"],"prefix":"10.1093","volume":"31","author":[{"given":"Guillaume","family":"Bouvier","sequence":"first","affiliation":[{"name":"Institut Pasteur, Unit\u00e9 de Bioinformatique Structurale; CNRS UMR 3528; D\u00e9partement de Biologie Structurale et Chimie; F-75015, Paris, France"}]},{"given":"Nathan","family":"Desdouits","sequence":"additional","affiliation":[{"name":"Institut Pasteur, Unit\u00e9 de Bioinformatique Structurale; CNRS UMR 3528; D\u00e9partement de Biologie Structurale et Chimie; F-75015, Paris, France"}]},{"given":"Mathias","family":"Ferber","sequence":"additional","affiliation":[{"name":"Institut Pasteur, Unit\u00e9 de Bioinformatique Structurale; CNRS UMR 3528; D\u00e9partement de Biologie Structurale et Chimie; F-75015, Paris, France"}]},{"given":"Arnaud","family":"Blondel","sequence":"additional","affiliation":[{"name":"Institut Pasteur, Unit\u00e9 de Bioinformatique Structurale; CNRS UMR 3528; D\u00e9partement de Biologie Structurale et Chimie; F-75015, Paris, France"}]},{"given":"Michael","family":"Nilges","sequence":"additional","affiliation":[{"name":"Institut Pasteur, Unit\u00e9 de Bioinformatique Structurale; CNRS UMR 3528; D\u00e9partement de Biologie Structurale et Chimie; F-75015, Paris, France"}]}],"member":"286","published-online":{"date-parts":[[2014,12,26]]},"reference":[{"key":"2023051308495687600_btu849-B1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1021\/ci400354b","article-title":"Functional motions modulating vana ligand binding unraveled by self-organizing maps","volume":"54","author":"Bouvier","year":"2014","journal-title":"J. Chem. Inf. Model."},{"key":"2023051308495687600_btu849-B2","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1016\/j.bpj.2009.06.047","article-title":"How does a simplified-sequence protein fold?","volume":"97","author":"Guarnera","year":"2009","journal-title":"Biophys. J."},{"key":"2023051308495687600_btu849-B3","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s10969-009-9062-2","article-title":"Distance matrix-based approach to protein structure prediction","volume":"10","author":"Kloczkowski","year":"2009","journal-title":"J. Struct. Funct. Genomics"},{"key":"2023051308495687600_btu849-B4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/1047-3203(90)90014-M","article-title":"Morphological segmentation","volume":"1","author":"Meyer","year":"1990","journal-title":"J. Visual Commun. Image Representation"},{"key":"2023051308495687600_btu849-B5","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1002\/prot.24412","article-title":"Stabilization of the integrase-dna complex by mg2\u2009+\u2009ions and prediction of key residues for binding hiv-1 integrase inhibitors","volume":"82","author":"Miri","year":"2014","journal-title":"Proteins"},{"key":"2023051308495687600_btu849-B6","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1016\/j.str.2014.03.001","article-title":"Distinct docking and stabilization steps of the pseudopilus conformational transition path suggest rotational assembly of type iv pilus-like fibers","volume":"22","author":"Nivaskumar","year":"2014","journal-title":"Structure"},{"key":"2023051308495687600_btu849-B7","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1002\/jcc.23113","article-title":"A convective replica-exchange method for sampling new energy basins","volume":"34","author":"Spill","year":"2013","journal-title":"J. Comput. Chem."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/31\/9\/1490\/50306203\/bioinformatics_31_9_1490.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/31\/9\/1490\/50306203\/bioinformatics_31_9_1490.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,13]],"date-time":"2023-05-13T08:50:57Z","timestamp":1683967857000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/31\/9\/1490\/200553"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,26]]},"references-count":7,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2015,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btu849","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2015,5,1]]},"published":{"date-parts":[[2014,12,26]]}}}