{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T21:29:22Z","timestamp":1778966962237,"version":"3.51.4"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1490,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Calmodulin (CaM) is a ubiquitously conserved protein that acts as a calcium sensor, and interacts with a large number of proteins. Detection of CaM binding proteins and their interaction sites experimentally requires a significant effort, so accurate methods for their prediction are important.<\/jats:p>\n               <jats:p>Results: We present a novel algorithm (MI-1 SVM) for binding site prediction and evaluate its performance on a set of CaM-binding proteins extracted from the Calmodulin Target Database. Our approach directly models the problem of binding site prediction as a large-margin classification problem, and is able to take into account uncertainty in binding site location. We show that the proposed algorithm performs better than the standard SVM formulation, and illustrate its ability to recover known CaM binding motifs. A highly accurate cascaded classification approach using the proposed binding site prediction method to predict CaM binding proteins in Arabidopsis thaliana is also presented.<\/jats:p>\n               <jats:p>Availability: Matlab code for training MI-1 SVM and the cascaded classification approach is available on request.<\/jats:p>\n               <jats:p>Contact: \u00a0fayyazafsar@gmail.com or asa@cs.colostate.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts416","type":"journal-article","created":{"date-parts":[[2012,9,7]],"date-time":"2012-09-07T20:35:22Z","timestamp":1347050122000},"page":"i416-i422","source":"Crossref","is-referenced-by-count":29,"title":["Multiple instance learning of Calmodulin binding sites"],"prefix":"10.1093","volume":"28","author":[{"given":"Fayyaz ul Amir Afsar","family":"Minhas","sequence":"first","affiliation":[{"name":"Department of Computer Science, Colorado State University, Fort Collins, CO 80523-1873, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asa","family":"Ben-Hur","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Colorado State University, Fort Collins, CO 80523-1873, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,9,3]]},"reference":[{"key":"2023012513011575000_B1","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic local alignment search tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J. Mol. Biol."},{"key":"2023012513011575000_B2","first-page":"561","article-title":"Support vector machines for multiple-instance learning","volume":"15","author":"Andrews","year":"2003","journal-title":"Adv. Neur. Inf. Process. Syst."},{"key":"2023012513011575000_B3","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.1109\/TPAMI.2010.226","article-title":"Robust object tracking with online multiple instance learning","volume":"33","author":"Babenko","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2023012513011575000_B4","article-title":"PyML - machine learning in Python","author":"Ben-Hur","year":"2011"},{"key":"2023012513011575000_B5","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1146\/annurev.arplant.56.032604.144224","article-title":"Plant-specific Calmodulin-binding proteins","volume":"56","author":"Bouche","year":"2005","journal-title":"Annu. Rev. Plant Biol."},{"key":"2023012513011575000_B6","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"2023012513011575000_B7","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0004-3702(96)00034-3","article-title":"Solving the multiple instance problem with axis-parallel rectangles","volume":"89","author":"Dietterich","year":"1997","journal-title":"Artif. Int."},{"key":"2023012513011575000_B8","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/1471-2105-10-48","article-title":"GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists","volume":"10","author":"den","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023012513011575000_B9","doi-asserted-by":"crossref","DOI":"10.1145\/2147805.2147855","article-title":"Kernel methods for Calmodulin binding and binding site prediction","volume-title":"ACM Conference on Bioinformatics, Computational Biology and Biomedicine","author":"Hamilton","year":"2011"},{"key":"2023012513011575000_B10","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1145\/1150402.1150429","article-title":"Training linear SVMs in linear time","volume-title":"Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Joachims","year":"2006"},{"key":"2023012513011575000_B11","first-page":"566","article-title":"The spectrum kernel: a string kernel for SVM protein classification","volume-title":"Pacific Symposium on Biocomputing","author":"Leslie","year":"2002"},{"key":"2023012513011575000_B12","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/0968-0004(90)90177-D","article-title":"How Calmodulin binds its targets: sequence independent recognition of amphiphilic alpha-helices","volume":"15","author":"O'Neil","year":"1990","journal-title":"Trends Biochem. Sci."},{"key":"2023012513011575000_B13","first-page":"4730","article-title":"Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays","volume":"104","author":"Popescu","year":"2007","journal-title":"Plant Biol."},{"key":"2023012513011575000_B14","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1002\/prot.20873","article-title":"Calmodulin signaling: analysis and prediction of a disorder-dependent molecular recognition","volume":"63","author":"Radivojac","year":"2006","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"2023012513011575000_B15","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1016\/j.phytochem.2010.12.022","article-title":"Experimental and computational approaches for the study of Calmodulin interactions","volume":"72","author":"Reddy","year":"2011","journal-title":"Phytochemistry"},{"key":"2023012513011575000_B16","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1145\/1015330.1015405","article-title":"SVM-based generalized multiple-instance learning via approximate box counting","volume-title":"Twenty-First International Conference on Machine Learning","author":"Tao","year":"2004"},{"key":"2023012513011575000_B17","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1016\/j.jmgm.2010.09.006","article-title":"Prediction of protein-ligand binding affinities using multiple instance learning","volume":"29","author":"Teramoto","year":"2010","journal-title":"J. Mol. Graph. Modell."},{"key":"2023012513011575000_B18","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1023\/A:1011320027914","article-title":"Calmodulin target database","volume":"1","author":"Yap","year":"2000","journal-title":"J. Struct. Funct. Genom."},{"key":"2023012513011575000_B19","doi-asserted-by":"crossref","first-page":"2203","DOI":"10.1093\/bioinformatics\/btm323","article-title":"Interaction-site prediction for protein complexes: a critical assessment","volume":"23","author":"Zhou","year":"2007","journal-title":"Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/18\/i416\/48880513\/bioinformatics_28_18_i416.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/18\/i416\/48880513\/bioinformatics_28_18_i416.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T18:49:06Z","timestamp":1674672546000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/28\/18\/i416\/251326"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,9,3]]},"references-count":19,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2012,9,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bts416","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2012,9,15]]},"published":{"date-parts":[[2012,9,3]]}}}