{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T14:08:57Z","timestamp":1776262137445,"version":"3.50.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Improvements in protein sequence annotation and an increase in the number of annotated protein databases has fueled development of an increasing number of software tools to predict secreted proteins. Six software programs capable of high throughput and employing a wide range of prediction methods, SignalP 3.0, SignalP 2.0, TargetP 1.01, PrediSi, Phobius, and ProtComp 6.0, are evaluated.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Prediction accuracies were evaluated using 372 unbiased, eukaryotic, SwissProt protein sequences. TargetP, SignalP 3.0 maximum S-score and SignalP 3.0 D-score were the most accurate single scores (90\u201391% accurate). The combination of a positive TargetP prediction, SignalP 2.0 maximum Y-score, and SignalP 3.0 maximum S-score increased accuracy by six percent.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Single predictive scores could be highly accurate, but almost all accuracies were slightly less than those reported by program authors. Predictive accuracy could be substantially improved by combining scores from multiple methods into a single composite prediction.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/1471-2105-6-256","type":"journal-article","created":{"date-parts":[[2005,10,15]],"date-time":"2005-10-15T18:13:53Z","timestamp":1129400033000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":63,"title":["Evaluating eukaryotic secreted protein prediction"],"prefix":"10.1186","volume":"6","author":[{"given":"Eric W","family":"Klee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lynda BM","family":"Ellis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2005,10,14]]},"reference":[{"key":"581_CR1","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1093\/bioinformatics\/16.8.741","volume":"16","author":"K Menne","year":"2000","unstructured":"Menne K, Hermjakob H, Apweiler R: A comparison of signal sequence prediction methods using a test set of signal peptides. Bioinformatics 2000, 16: 741\u2013742. 10.1093\/bioinformatics\/16.8.741","journal-title":"Bioinformatics"},{"key":"581_CR2","doi-asserted-by":"publisher","first-page":"2819","DOI":"10.1110\/ps.04682504","volume":"13","author":"Z Zhang","year":"2004","unstructured":"Zhang Z, Henzel WJ: Signal peptide prediction based on analysis of experimentally verified cleavage sites. Protein Sci 2004, 13: 2819\u201324. 10.1110\/ps.04682504","journal-title":"Protein Sci"},{"key":"581_CR3","first-page":"17","volume":"1694","author":"J Luirink","year":"2004","unstructured":"Luirink J, Sinning I: SRP-mediated protein targeting: structure and function revisited. Biochim Biophys Acta 2004, 1694: 17\u201335.","journal-title":"Biochim Biophys Acta"},{"key":"581_CR4","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1016\/j.jmb.2004.05.028","volume":"340","author":"JD Bendtsen","year":"2004","unstructured":"Bendtsen JD, Nielsen H, von Heijne G, Brunak S: Improved prediction of signal peptides: SignalP 3.0. J Mol Biol 2004, 340: 783\u2013795. 10.1016\/j.jmb.2004.05.028","journal-title":"J Mol Biol"},{"key":"581_CR5","first-page":"122","volume":"6","author":"H Nielsen","year":"1998","unstructured":"Nielsen H, Krogh A: Prediction of signal peptides and signal anchors by a hidden Markov model. Proc Int Conf Intell Syst Mol Biol 1998, 6: 122\u2013130.","journal-title":"Proc Int Conf Intell Syst Mol Biol"},{"key":"581_CR6","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1006\/jmbi.2000.3903","volume":"300","author":"O Emanuelsson","year":"2000","unstructured":"Emanuelsson O, Nielsen H, Brunak S, von Heijne G: Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 2000, 300: 1005\u20131016. 10.1006\/jmbi.2000.3903","journal-title":"J Mol Biol"},{"key":"581_CR7","doi-asserted-by":"publisher","first-page":"W375","DOI":"10.1093\/nar\/gkh378","volume":"32","author":"K Hiller","year":"2004","unstructured":"Hiller K, Grote A, Scheer M, Munch R, Jahn D: PrediSi: prediction of signal peptides and their cleavage positions. Nucleic Acids Res 2004, 32: W375\u20139.","journal-title":"Nucleic Acids Res"},{"key":"581_CR8","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1016\/j.jmb.2004.03.016","volume":"338","author":"L Kall","year":"2004","unstructured":"Kall L, Krogh A, Sonnhammer EL: A combined transmembrane topology and signal peptide prediction method. J Mol Biol 2004, 338: 1027\u201336. 10.1016\/j.jmb.2004.03.016","journal-title":"J Mol Biol"},{"key":"581_CR9","unstructured":"Softberry ProtComp 6.0[http:\/\/www.softberry.com\/berry.phtml?topic=protcompan&group=help&subgroup=proloc]"},{"key":"581_CR10","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1093\/protein\/12.1.3","volume":"12","author":"H Nielsen","year":"1999","unstructured":"Nielsen H, Brunak S, von Heijne G: Machine learning approaches for the prediction of signal peptides and other protein sorting signals. Protein Eng 1999, 12: 3\u20139. 10.1093\/protein\/12.1.3","journal-title":"Protein Eng"},{"key":"581_CR11","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/S0167-4889(01)00145-8","volume":"1541","author":"O Emanuelsson","year":"2001","unstructured":"Emanuelsson O, von Heijne G: Prediction of organellar targeting signals. Biochim Biophys Acta 2001, 1541: 114\u20139. 10.1016\/S0167-4889(01)00145-8","journal-title":"Biochim Biophys Acta"},{"key":"581_CR12","doi-asserted-by":"publisher","first-page":"2819","DOI":"10.1110\/ps.04682504","volume":"13","author":"Z Zhang","year":"2004","unstructured":"Zhang Z, Henzel WJ: Signal peptide prediction based on analysis of experimentally verified cleavage sites. Protein Sci 2004, 13: 2819\u201324. 10.1110\/ps.04682504","journal-title":"Protein Sci"},{"key":"581_CR13","doi-asserted-by":"publisher","first-page":"4683","DOI":"10.1093\/nar\/14.11.4683","volume":"14","author":"G von Heijne","year":"1986","unstructured":"von Heijne G: A new method for predicting signal sequence cleavage sites. Nucleic Acids Res 1986, 14: 4683\u201390.","journal-title":"Nucleic Acids Res"},{"key":"581_CR14","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/0022-2836(85)90046-4","volume":"184","author":"G von Heijne","year":"1985","unstructured":"von Heijne G: Signal sequences. The limits of variation. J Mol Biol 1985, 184: 99\u2013105. 10.1016\/0022-2836(85)90046-4","journal-title":"J Mol Biol"},{"key":"581_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/protein\/10.1.1","volume":"10","author":"H Nielsen","year":"1997","unstructured":"Nielsen H, Engelbrecht J, Brunak S, von Heijne G: Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Protein Eng 1997, 10: 1\u20136. 10.1093\/protein\/10.1.1","journal-title":"Protein Eng"},{"key":"581_CR16","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1093\/protein\/gzh013","volume":"17","author":"P Duckert","year":"2004","unstructured":"Duckert P, Brunak S, Blom N: Prediction of proprotein convertase cleavage sites. Protein Eng Des Sel 2004, 17: 107\u2013112. 10.1093\/protein\/gzh013","journal-title":"Protein Eng Des Sel"},{"key":"581_CR17","doi-asserted-by":"publisher","first-page":"978","DOI":"10.1110\/ps.8.5.978","volume":"8","author":"O Emanuelsson","year":"1999","unstructured":"Emanuelsson O, Nielsen H, von Heijne G: ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci 1999, 8: 978\u2013984.","journal-title":"Protein Sci"},{"key":"581_CR18","doi-asserted-by":"publisher","first-page":"897","DOI":"10.1016\/S0888-7543(05)80111-9","volume":"14","author":"K Nakai","year":"1992","unstructured":"Nakai K, Kanehisa M: A knowledge base for predicting protein localization sites in eukaryotic cells. Genomics 1992, 14: 897\u2013911. 10.1016\/S0888-7543(05)80111-9","journal-title":"Genomics"},{"key":"581_CR19","first-page":"147","volume":"5","author":"P Horton","year":"1997","unstructured":"Horton P, Nakai K: Better prediction of protein cellular localization sites with the k nearest neighbors classifier. Proc Int Conf Intell Syst Mol Biol 1997, 5: 147\u2013152.","journal-title":"Proc Int Conf Intell Syst Mol Biol"},{"key":"581_CR20","first-page":"441","volume":"11","author":"MG Claros","year":"1995","unstructured":"Claros MG: MitoProt: a Macintosh application for studying mitochondrial proteins. Comput Appl Biosci 1995, 11: 441\u2013447.","journal-title":"Comput Appl Biosci"},{"key":"581_CR21","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1111\/j.1432-1033.1996.00779.x","volume":"241","author":"MG Claros","year":"1996","unstructured":"Claros MG, Vincens P: Computational method to predict mitochondrially imported proteins and their targeting sequences. Eur J Biochem 1996, 241: 779\u2013786. 10.1111\/j.1432-1033.1996.00779.x","journal-title":"Eur J Biochem"},{"key":"581_CR22","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1006\/jmbi.2000.4315","volume":"305","author":"A Krogh","year":"2001","unstructured":"Krogh A, Larsson B, von Heijne G, Sonnhammer EL: Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol 2001, 305: 567\u201380. 10.1006\/jmbi.2000.4315","journal-title":"J Mol Biol"},{"key":"581_CR23","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1093\/nar\/gkg020","volume":"31","author":"M Ikeda","year":"2003","unstructured":"Ikeda M, Arai M, Okuno T, Shimizu T: TMPDB: a database of experimentally-characterized transmembrane topologies. Nucl Acids Res 2003, 31: 406\u2013409. 10.1093\/nar\/gkg020","journal-title":"Nucl Acids Res"},{"key":"581_CR24","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1093\/bioinformatics\/16.12.1159","volume":"16","author":"S Moller","year":"2000","unstructured":"Moller S, Kriventseva EV, Apweiler R: A collection of well characterised integral membrane proteins. Bioinformatics 2000, 16: 1159\u20131160. 10.1093\/bioinformatics\/16.12.1159","journal-title":"Bioinformatics"},{"key":"581_CR25","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1016\/0005-2795(75)90109-9","volume":"405","author":"BW Matthews","year":"1975","unstructured":"Matthews BW: Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta 1975, 405: 442\u2013451.","journal-title":"Biochim Biophys Acta"},{"key":"581_CR26","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1093\/bioinformatics\/16.5.412","volume":"16","author":"P Baldi","year":"2000","unstructured":"Baldi P, Brunak S, Chauvin Y, Andersen CAF, Nielsen H: Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 2000, 16: 412\u2013424. 10.1093\/bioinformatics\/16.5.412","journal-title":"Bioinformatics"},{"key":"581_CR27","unstructured":"Vertebrate Secretome and CTT-ome Database[http:\/\/www.secretomes.umn.edu]"},{"key":"581_CR28","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1093\/biomet\/36.3-4.394","volume":"36","author":"FN David","year":"1949","unstructured":"David FN: The Moments of the z and F Distributions. Biometrika 1949, 36: 394\u2013403.","journal-title":"Biometrika"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-6-256.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T17:46:30Z","timestamp":1706809590000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-6-256"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,10,14]]},"references-count":28,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2005,12]]}},"alternative-id":["581"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-6-256","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,10,14]]},"assertion":[{"value":"15 March 2005","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2005","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2005","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"256"}}