M. Zare, H. Mohabatkar, Fatemeh Faramarzi, Majid Mohammad Beigi, M. Behbahani
{"title":"Using Chou’s Pseudo Amino Acid Composition and Machine LearningMethod to Predict the Antiviral Peptides","authors":"M. Zare, H. Mohabatkar, Fatemeh Faramarzi, Majid Mohammad Beigi, M. Behbahani","doi":"10.2174/1875036201509010013","DOIUrl":null,"url":null,"abstract":"Traditional antiviral therapies are expensive, limitedly available, and cause several side effects. Currently, de- signing antiviral peptides is very important, because these peptides interfere with the key stage of virus life cycle. Most of the antiviral peptides are derived from viral proteins for example peptide derived from HIV-1 capsid protein. Because of the importance of these peptides, in this study the concept of pseudo-amino acid composition (PseAAC) and machine learning methods are used to classify or identify antiviral peptides.","PeriodicalId":38956,"journal":{"name":"Open Bioinformatics Journal","volume":"9 1","pages":"13-19"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Bioinformatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1875036201509010013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 21
Abstract
Traditional antiviral therapies are expensive, limitedly available, and cause several side effects. Currently, de- signing antiviral peptides is very important, because these peptides interfere with the key stage of virus life cycle. Most of the antiviral peptides are derived from viral proteins for example peptide derived from HIV-1 capsid protein. Because of the importance of these peptides, in this study the concept of pseudo-amino acid composition (PseAAC) and machine learning methods are used to classify or identify antiviral peptides.
期刊介绍：
The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.
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