{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:50:33Z","timestamp":1775325033155,"version":"3.50.1"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2004,2,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Prediction of peptides binding with MHC class II allele HLA-DRB1*0401 can effectively reduce the number of experiments required for identifying helper T cell epitopes. This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1*0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique.<\/jats:p>\n               <jats:p>Available: A web server HLA-DR4Pred based on above approach is available at http:\/\/www.imtech.res.in\/raghava\/hladr4pred\/ and http:\/\/bioinformatics.uams.edu\/mirror\/hladr4pred\/ (Mirror Site).<\/jats:p>\n               <jats:p>Supplementary information: \u00a0http:\/\/www.imtech.res.in\/raghava\/hladr4pred\/info.html<\/jats:p>","DOI":"10.1093\/bioinformatics\/btg424","type":"journal-article","created":{"date-parts":[[2004,2,11]],"date-time":"2004-02-11T16:52:44Z","timestamp":1076518364000},"page":"421-423","source":"Crossref","is-referenced-by-count":131,"title":["SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence"],"prefix":"10.1093","volume":"20","author":[{"given":"Manoj","family":"Bhasin","sequence":"first","affiliation":[]},{"given":"G. P. S.","family":"Raghava","sequence":"additional","affiliation":[]}],"member":"286","published-online":{"date-parts":[[2004,1,22]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/3\/421\/48905183\/bioinformatics_20_3_421.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/3\/421\/48905183\/bioinformatics_20_3_421.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T18:21:16Z","timestamp":1674670876000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/20\/3\/421\/186291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,1,22]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2004,2,12]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btg424","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2004,2,12]]},"published":{"date-parts":[[2004,1,22]]}}}