{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T16:07:13Z","timestamp":1707754033338},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Most proteins contain compositionally biased segments (CBS) in which one or more amino acid types are significantly overrepresented. CBS that contain amino acids with similar chemical properties can have functional and structural importance. This article describes ProBias, a web-server that searches a protein sequence for CBS composed of user-specified amino acid types. ProBias utilizes the discrete scan statistics to estimate statistical significance of CBS and is able to detect even subtle local deviations from the random independence model. The web-server also analyzes the global compositional bias of the input sequence. In the case of novel proteins that lack functional annotation, statistically significant CBS reported by ProBias can be used to guide the search for potential functionally important sites or domains.<\/jats:p>\n               <jats:p>Availability: Freely available at http:\/\/lcg.rit.albany.edu\/ProBias<\/jats:p>\n               <jats:p>Contact: \u00a0IKuznetsov@albany.edu<\/jats:p>\n               <jats:p>Supplemantary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btn233","type":"journal-article","created":{"date-parts":[[2008,5,15]],"date-time":"2008-05-15T00:34:38Z","timestamp":1210811678000},"page":"1534-1535","source":"Crossref","is-referenced-by-count":4,"title":["ProBias: a web-server for the identification of user-specified types of compositionally biased segments in protein sequences"],"prefix":"10.1093","volume":"24","author":[{"given":"Igor B.","family":"Kuznetsov","sequence":"first","affiliation":[{"name":"Gen\u22c6NY\u22c6sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, One Discovery Drive, University at Albany, Rensselaer, NY 12144, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2008,5,14]]},"reference":[{"key":"2023020210350728600_B1","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1093\/bioinformatics\/18.5.672","article-title":"Detecting cryptically simple protein sequences using the SIMPLE algorithm","volume":"8","author":"Alba","year":"2002","journal-title":"Bioinformatics"},{"key":"2023020210350728600_B2","doi-asserted-by":"crossref","first-page":"2002","DOI":"10.1073\/pnas.89.6.2002","article-title":"Methods and algorithms for statistical analysis of protein sequences","volume":"89","author":"Brendel","year":"1992","journal-title":"Proc. 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