{"title":"Automated Identifying Intrinsic Unstructured Regions in Proteins - A Software Tool","authors":"J.Y. Yang, M. Qu Yang, Zuojie Luo, O. Ersoy","doi":"10.1109/CIMA.2005.1662361","DOIUrl":null,"url":null,"abstract":"In our attempts to construct methods for automated structural and functional annotation of proteins, the prediction of intrinsically unstructured/disordered protein (IUP) regions, i.e. those with a lack of stable secondary or tertiary structure, has recently gained importance. We developed a software tool for identifying IUP and structured protein regions. The predictor uses both supervised and unsupervised learning techniques and both structural and motional information of amino acids. We demonstrate the effectiveness of our IUP predictor which utilizes feature selection, bootstrapping aggregation, boosting and consensus networking algorithms","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 ICSC Congress on Computational Intelligence Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMA.2005.1662361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In our attempts to construct methods for automated structural and functional annotation of proteins, the prediction of intrinsically unstructured/disordered protein (IUP) regions, i.e. those with a lack of stable secondary or tertiary structure, has recently gained importance. We developed a software tool for identifying IUP and structured protein regions. The predictor uses both supervised and unsupervised learning techniques and both structural and motional information of amino acids. We demonstrate the effectiveness of our IUP predictor which utilizes feature selection, bootstrapping aggregation, boosting and consensus networking algorithms