{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,6]],"date-time":"2023-10-06T12:00:40Z","timestamp":1696593640598},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,3,15]]},"abstract":"Abstract<\/jats:title>\n Motivation:\u2003Meaningful scores to assess protein structure similarity are essential to decipher protein structure and sequence evolution. The mining of the increasing number of protein structures requires fast and accurate similarity measures with statistical significance. Whereas numerous approaches have been proposed for protein domains as a whole, the focus is progressively moving to a more local level of structure analysis for which similarity measurement still remains without any satisfactory answer.<\/jats:p>\n Results:\u2003We introduce a new score based on Binet\u2013Cauchy kernel. It is normalized and bounded between 1\u2014maximal similarity that implies exactly the same conformations for protein fragments\u2014and \u22121\u2014mirror image conformations, the unrelated conformations having a null mean score. This allows for the search of both similar and mirror conformations. In addition, such score addresses two major issue of the widely used root mean square deviation (RMSD). First, it achieves length independent statistics even for short fragments. Second, it shows better performance in the discrimination of medium range RMSD values. Being simpler and faster to compute than the RMSD, it also provides the means for large-scale mining of protein structures.<\/jats:p>\n Availability and implementation:\u2003The computer software implementing the score is available at http:\/\/bioserv.rpbs.univ-paris-diderot.fr\/BCscore\/<\/jats:p>\n Contact:\u2003frederic.guyon@univ-paris-diderot.fr<\/jats:p>\n Supplementary Information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt618","type":"journal-article","created":{"date-parts":[[2013,10,29]],"date-time":"2013-10-29T00:39:39Z","timestamp":1383007179000},"page":"784-791","source":"Crossref","is-referenced-by-count":17,"title":["Fast protein fragment similarity scoring using a Binet\u2013Cauchy kernel"],"prefix":"10.1093","volume":"30","author":[{"given":"Fr\u00e9d\u00e9ric","family":"Guyon","sequence":"first","affiliation":[{"name":"1 Univ Paris Diderot, Sorbonne Paris Cit\u00e9, Mol\u00e9cules Th\u00e9rapeutiques in Silico, UMR 973, F-75205 Paris, France, 2INSERM, U973, F-75205 Paris, France and 3Univ Paris Diderot, Ressources Parisiennes de Bioinformatique Structurale, F-75205 Paris, France"}]},{"given":"Pierre","family":"Tuff\u00e9ry","sequence":"additional","affiliation":[{"name":"1 Univ Paris Diderot, Sorbonne Paris Cit\u00e9, Mol\u00e9cules Th\u00e9rapeutiques in Silico, UMR 973, F-75205 Paris, France, 2INSERM, U973, F-75205 Paris, France and 3Univ Paris Diderot, Ressources Parisiennes de Bioinformatique Structurale, F-75205 Paris, France"},{"name":"1 Univ Paris Diderot, Sorbonne Paris Cit\u00e9, Mol\u00e9cules Th\u00e9rapeutiques in Silico, UMR 973, F-75205 Paris, France, 2INSERM, U973, F-75205 Paris, France and 3Univ Paris Diderot, Ressources Parisiennes de Bioinformatique Structurale, F-75205 Paris, France"},{"name":"1 Univ Paris Diderot, Sorbonne Paris Cit\u00e9, Mol\u00e9cules Th\u00e9rapeutiques in Silico, UMR 973, F-75205 Paris, France, 2INSERM, U973, F-75205 Paris, France and 3Univ Paris Diderot, Ressources Parisiennes de Bioinformatique Structurale, F-75205 Paris, France"}]}],"member":"286","published-online":{"date-parts":[[2013,10,27]]},"reference":[{"key":"2023012710442742400_btt618-B1","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1214\/aop\/1176996548","article-title":"Residual life time at great age","volume":"2","author":"Balkema","year":"1974","journal-title":"Ann. 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