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Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>We propose to identify and group similar profiles using two independent similarity measures: <jats:italic>\u03c7<\/jats:italic><jats:sup>2<\/jats:sup> distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusion<\/jats:title>\n                        <jats:p>We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/1471-2105-6-237","type":"journal-article","created":{"date-parts":[[2005,9,30]],"date-time":"2005-09-30T18:14:11Z","timestamp":1128104051000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Measuring similarities between transcription factor binding sites"],"prefix":"10.1186","volume":"6","author":[{"given":"Szymon M","family":"Kielbasa","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Didier","family":"Gonze","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanspeter","family":"Herzel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2005,9,28]]},"reference":[{"issue":"4","key":"562_CR1","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1038\/nrg1315","volume":"5","author":"W Wasserman","year":"2004","unstructured":"Wasserman W, Sandelin A: Applied bioinformatics for the identification of regulatory elements. 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