{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T20:45:35Z","timestamp":1788468335248,"version":"build-2803163510"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and\/or the motifs are found at different locations within distinct peptides.<\/jats:p>\n               <jats:p>Results: The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities in peptide data by performing two essential tasks simultaneously: alignment and clustering of peptide data. We apply the method to de-convolute binding motifs in a panel of peptide datasets with different degrees of complexity spanning from the simplest case of pre-aligned fixed-length peptides to cases of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule.<\/jats:p>\n               <jats:p>Availability: The Gibbs clustering method is available online as a web server at http:\/\/www.cbs.dtu.dk\/services\/GibbsCluster.<\/jats:p>\n               <jats:p>Contact: \u00a0massimo@cbs.dtu.dk<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts621","type":"journal-article","created":{"date-parts":[[2012,10,24]],"date-time":"2012-10-24T20:56:29Z","timestamp":1351112189000},"page":"8-14","source":"Crossref","is-referenced-by-count":149,"title":["Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach"],"prefix":"10.1093","volume":"29","author":[{"given":"Massimo","family":"Andreatta","sequence":"first","affiliation":[{"name":"1 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark and 2Instituto de Investigaciones Biotecnol\u00f3gicas, Universidad de San Mart\u00edn, CP 1650 San Mart\u00edn, Buenos Aires, Argentina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ole","family":"Lund","sequence":"additional","affiliation":[{"name":"1 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark and 2Instituto de Investigaciones Biotecnol\u00f3gicas, Universidad de San Mart\u00edn, CP 1650 San Mart\u00edn, Buenos Aires, Argentina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Morten","family":"Nielsen","sequence":"additional","affiliation":[{"name":"1 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark and 2Instituto de Investigaciones Biotecnol\u00f3gicas, Universidad de San Mart\u00edn, CP 1650 San Mart\u00edn, Buenos Aires, Argentina"},{"name":"1 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark and 2Instituto de Investigaciones Biotecnol\u00f3gicas, Universidad de San Mart\u00edn, CP 1650 San Mart\u00edn, Buenos Aires, Argentina"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2012,10,24]]},"reference":[{"key":"2023020303204959800_bts621-B1","doi-asserted-by":"crossref","first-page":"e26781","DOI":"10.1371\/journal.pone.0026781","article-title":"NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data","volume":"6","author":"Andreatta","year":"2011","journal-title":"PLoS One"},{"key":"2023020303204959800_bts621-B2","doi-asserted-by":"crossref","first-page":"7890","DOI":"10.4049\/jimmunol.178.12.7890","article-title":"A quantitative analysis of the variables affecting the repertoire of T cell specificities recognized after vaccinia virus infection","volume":"178","author":"Assarsson","year":"2007","journal-title":"J. Immunol."},{"key":"2023020303204959800_bts621-B3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/BF00993379","article-title":"Unsupervised learning of multiple motifs in biopolymers using expectation maximization","volume":"21","author":"Bailey","year":"1995","journal-title":"Mach. Learn."},{"key":"2023020303204959800_bts621-B4","doi-asserted-by":"crossref","first-page":"W369","DOI":"10.1093\/nar\/gkl198","article-title":"MEME: discovering and analyzing DNA and protein sequence motifs","volume":"34","author":"Bailey","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"2023020303204959800_bts621-B5","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1007\/s00018-009-0192-2","article-title":"Progress in phage display: evolution of the technique and its applications","volume":"67","author":"Bratkovi\u010d","year":"2010","journal-title":"Cell. Mol. Life Sci."},{"key":"2023020303204959800_bts621-B6","doi-asserted-by":"crossref","first-page":"4441","DOI":"10.4049\/jimmunol.160.9.4441","article-title":"MHC class I\/peptide stability: implications for immunodominance, in vitro proliferation, and diversity of responding CTL","volume":"160","author":"Busch","year":"1998","journal-title":"J. Immunol."},{"key":"2023020303204959800_bts621-B7","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.biotechadv.2011.06.012","article-title":"The protein interaction network mediated by human SH3 domains","volume":"30","author":"Carducci","year":"2012","journal-title":"Biotechnol. Adv."},{"key":"2023020303204959800_bts621-B8","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1016\/j.febslet.2012.03.045","article-title":"Stability of peptide-HLA-I complexes and tapasin folding facilitation\u2014tools to define immunogenic peptides","volume":"586","author":"Geironson","year":"2012","journal-title":"FEBS Lett."},{"key":"2023020303204959800_bts621-B9","doi-asserted-by":"crossref","first-page":"2764","DOI":"10.1016\/j.febslet.2012.03.054","article-title":"Uncovering new aspects of protein interactions through analysis of specificity landscapes in peptide recognition domains","volume":"586","author":"Gfeller","year":"2012","journal-title":"FEBS Lett."},{"key":"2023020303204959800_bts621-B10","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/msb.2011.18","article-title":"The multiple-specificity landscape of molecular peptide recognition domains","volume":"7","author":"Gfeller","year":"2011","journal-title":"Mol. Syst. Biol."},{"key":"2023020303204959800_bts621-B11","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.M110.000786","article-title":"Exploring antibody recognition of sequence space through random-sequence peptide microarrays","volume":"10","author":"Halperin","year":"2011","journal-title":"Mol. Cell. Proteomics"},{"key":"2023020303204959800_bts621-B12","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1002\/eji.201141774","article-title":"Peptide-MHC class I stability is a better predictor than peptide affinity of CTL immunogenicity","volume":"42","author":"Harndahl","year":"2012","journal-title":"Eur. J. Immunol."},{"key":"2023020303204959800_bts621-B13","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF01908075","article-title":"Comparing partitions","volume":"2","author":"Hubert","year":"1985","journal-title":"J. Classif."},{"key":"2023020303204959800_bts621-B14","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s00251-011-0579-8","article-title":"NetMHCcons: a consensus method for the major histocompatibility complex class I predictions","volume":"64","author":"Karosiene","year":"2012","journal-title":"Immunogenetics"},{"key":"2023020303204959800_bts621-B15","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkr1294","article-title":"MUSI: an integrated system for identifying multiple specificity from large peptide or nucleic acid data sets","volume":"40","author":"Kim","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"2023020303204959800_bts621-B16","first-page":"883","article-title":"Identification of receptor ligands with phage display peptide libraries","volume":"40","author":"Koivunen","year":"1999","journal-title":"J. Nucl. Med."},{"key":"2023020303204959800_bts621-B17","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1126\/science.8211139","article-title":"Detecting subtle sequence signals: a gibbs sampling strategy for multiple alignment","volume":"262","author":"Lawrence","year":"1993","journal-title":"Science"},{"key":"2023020303204959800_bts621-B18","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1007\/s00251-004-0647-4","article-title":"Definition of supertypes for HLA molecules using clustering of specificity matrices","volume":"55","author":"Lund","year":"2004","journal-title":"Immunogenetics"},{"key":"2023020303204959800_bts621-B19","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1242\/jcs.114.7.1253","article-title":"SH3 domains: complexity in moderation","volume":"114","author":"Mayer","year":"2001","journal-title":"J. Cell Sci."},{"key":"2023020303204959800_bts621-B20","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1186\/1471-2105-10-296","article-title":"NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction","volume":"10","author":"Nielsen","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023020303204959800_bts621-B22","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1093\/bioinformatics\/bth100","article-title":"Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach","volume":"20","author":"Nielsen","year":"2004","journal-title":"Bioinformatics"},{"key":"2023020303204959800_bts621-B23","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/S1389-1723(02)80160-8","article-title":"Hidden Markov model-based prediction of antigenic peptides that interact with MHC class II molecules","volume":"94","author":"Noguchi","year":"2002","journal-title":"J. Biosci. Bioeng."},{"key":"2023020303204959800_bts621-B24","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s002510050595","article-title":"SYFPEITHI: database for MHC ligands and peptide motifs","volume":"50","author":"Rammensee","year":"1999","journal-title":"Immunogenetics"},{"key":"2023020303204959800_bts621-B25","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1080\/01621459.1971.10482356","article-title":"Objective criteria for the evaluation of clustering methods","volume":"66","author":"Rand","year":"1971","journal-title":"J. Am. Stat. Assoc."},{"key":"2023020303204959800_bts621-B26","doi-asserted-by":"crossref","first-page":"1526","DOI":"10.4049\/jimmunol.182.3.1526","article-title":"A comparative study of HLA binding affinity and ligand diversity: implications for generating immunodominant CD8+ T cell responses","volume":"182","author":"Rao","year":"2009","journal-title":"J. Immunol."},{"key":"2023020303204959800_bts621-B27","doi-asserted-by":"crossref","first-page":"2609","DOI":"10.1016\/j.febslet.2012.04.042","article-title":"SH3 domain ligand specificity: what's the consensus and where's the specificity","volume":"586","author":"Saksela","year":"2012","journal-title":"FEBS Lett."},{"key":"2023020303204959800_bts621-B28","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1002\/cbic.200400314","article-title":"Peptide arrays for kinase profiling","volume":"6","author":"Schutkowski","year":"2005","journal-title":"ChemBioChem"},{"key":"2023020303204959800_bts621-B29","doi-asserted-by":"crossref","first-page":"e65","DOI":"10.1371\/journal.pbio.0000065","article-title":"Detection and characterization of cellular immune responses using peptide-MHC microarrays","volume":"1","author":"Soen","year":"2003","journal-title":"PLoS Biol."},{"key":"2023020303204959800_bts621-B30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/nar\/gks469","article-title":"Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion","volume":"40","author":"Thomsen","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"2023020303204959800_bts621-B31","doi-asserted-by":"crossref","first-page":"2428","DOI":"10.2174\/138161208785777450","article-title":"Peptide microarrays: next generation biochips for detection, diagnostics and high-throughput screening","volume":"14","author":"Uttamchandani","year":"2008","journal-title":"Curr. Pharm. Des."},{"key":"2023020303204959800_bts621-B33","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1186\/1471-2105-11-568","article-title":"Peptide binding predictions for HLA DR, DP and DQ molecules","volume":"11","author":"Wang","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023020303204959800_bts621-B34","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1146\/annurev.cellbio.15.1.579","article-title":"Mechanisms of viral interference with MHC class I antigen processing and presentation","volume":"15","author":"Yewdell","year":"1999","journal-title":"Annu. Rev. Cell Dev. Biol."},{"key":"2023020303204959800_bts621-B35","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1016\/0092-8674(94)90367-0","article-title":"Structural basis for the binding of proline-rich peptides to SH3 domains","volume":"76","author":"Yu","year":"1994","journal-title":"Cell"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/29\/1\/8\/49060457\/bioinformatics_29_1_8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/29\/1\/8\/49060457\/bioinformatics_29_1_8.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T22:22:42Z","timestamp":1675376562000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/29\/1\/8\/272260"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,10,24]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bts621","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2013,1]]},"published":{"date-parts":[[2012,10,24]]}}}