{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T02:50:27Z","timestamp":1791946227582,"version":"4.3.4"},"reference-count":112,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T00:00:00Z","timestamp":1573776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The TRF Research Grant for New Scholar from the Thailand Research Fund","award":["MRG6180226"],"award-info":[{"award-number":["MRG6180226"]}]},{"name":"The TRF Research Career Development Grant from the Thailand Research Fund","award":["RSA6280075"],"award-info":[{"award-number":["RSA6280075"]}]},{"name":"The Office of Higher Education Commission and Mahidol University","award":["-"],"award-info":[{"award-number":["-"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>In spite of the large-scale production and widespread distribution of vaccines and antiviral drugs, viruses remain a prominent human disease. Recently, the discovery of antiviral peptides (AVPs) has become an influential antiviral agent due to their extraordinary advantages. With the avalanche of newly-found peptide sequences in the post-genomic era, there is a great demand to develop a sequence-based predictor for timely identifying AVPs as this information is very useful for both basic research and drug development. In this study, we propose a novel sequence-based meta-predictor with an effective feature representation, called Meta-iAVP, for the accurate prediction of AVPs from given peptide sequences. Herein, the effective feature representation was extracted from a set of prediction scores derived from various machine learning algorithms and types of features. To the best of our knowledge, the model proposed herein represents the first meta-based approach for the prediction of AVPs. An overall accuracy and Matthews correlation coefficient of 95.20% and 0.90, respectively, was achieved from the independent test set on an objective benchmark dataset. Comparative analysis suggested that Meta-iAVP was superior to that of existing methods and therefore represents a useful tool for AVP prediction. Finally, in an effort to facilitate high-throughput prediction of AVPs, the model was deployed as the Meta-iAVP web server and is made freely available online at http:\/\/codes.bio\/meta-iavp\/ where users can submit query peptide sequences for determining the likelihood of whether or not these peptides are AVPs.<\/jats:p>","DOI":"10.3390\/ijms20225743","type":"journal-article","created":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T11:25:56Z","timestamp":1573817156000},"page":"5743","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":137,"title":["Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation"],"prefix":"10.3390","volume":"20","author":[{"given":"Nalini","family":"Schaduangrat","sequence":"first","affiliation":[{"name":"Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1040-663X","authenticated-orcid":false,"given":"Chanin","family":"Nantasenamat","sequence":"additional","affiliation":[{"name":"Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Virapong","family":"Prachayasittikul","sequence":"additional","affiliation":[{"name":"Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3394-8709","authenticated-orcid":false,"given":"Watshara","family":"Shoombuatong","sequence":"additional","affiliation":[{"name":"Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"D1147","DOI":"10.1093\/nar\/gkt1191","article-title":"AVPdb: A database of experimentally validated antiviral peptides targeting medically important viruses","volume":"42","author":"Qureshi","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"ref_2","unstructured":"(2019, January 23). 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