Denilson Fagundes Barbosa, Liliane Santana Oliveira, Pedro Gabriel Nachtigall, Rodolpho Valentini Junior, Nayane de Souza, Alexandre Rossi Paschoal, André Yoshiaki Kashiwabara
{"title":"cirCodAn: A GHMM-based tool for accurate prediction of coding regions in circRNA.","authors":"Denilson Fagundes Barbosa, Liliane Santana Oliveira, Pedro Gabriel Nachtigall, Rodolpho Valentini Junior, Nayane de Souza, Alexandre Rossi Paschoal, André Yoshiaki Kashiwabara","doi":"10.1016/bs.apcsb.2023.11.012","DOIUrl":null,"url":null,"abstract":"<p><p>Studies focusing on characterizing circRNAs with the potential to translate into peptides are quickly advancing. It is helping to elucidate the roles played by circRNAs in several biological processes, especially in the emergence and development of diseases. While various tools are accessible for predicting coding regions within linear sequences, none have demonstrated accurate open reading frame detection in circular sequences, such as circRNAs. Here, we present cirCodAn, a novel tool designed to predict coding regions in circRNAs. We evaluated the performance of cirCodAn using datasets of circRNAs with strong translation evidence and showed that cirCodAn outperformed the other tools available to perform a similar task. Our findings demonstrate the applicability of cirCodAn to identify coding regions in circRNAs, which reveals the potential of use of cirCodAn in future research focusing on elucidating the biological roles of circRNAs and their encoded proteins. cirCodAn is freely available at https://github.com/denilsonfbar/cirCodAn.</p>","PeriodicalId":7376,"journal":{"name":"Advances in protein chemistry and structural biology","volume":"139 ","pages":"289-334"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in protein chemistry and structural biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/bs.apcsb.2023.11.012","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/17 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
Abstract
Studies focusing on characterizing circRNAs with the potential to translate into peptides are quickly advancing. It is helping to elucidate the roles played by circRNAs in several biological processes, especially in the emergence and development of diseases. While various tools are accessible for predicting coding regions within linear sequences, none have demonstrated accurate open reading frame detection in circular sequences, such as circRNAs. Here, we present cirCodAn, a novel tool designed to predict coding regions in circRNAs. We evaluated the performance of cirCodAn using datasets of circRNAs with strong translation evidence and showed that cirCodAn outperformed the other tools available to perform a similar task. Our findings demonstrate the applicability of cirCodAn to identify coding regions in circRNAs, which reveals the potential of use of cirCodAn in future research focusing on elucidating the biological roles of circRNAs and their encoded proteins. cirCodAn is freely available at https://github.com/denilsonfbar/cirCodAn.
期刊介绍:
Published continuously since 1944, The Advances in Protein Chemistry and Structural Biology series has been the essential resource for protein chemists. Each volume brings forth new information about protocols and analysis of proteins. Each thematically organized volume is guest edited by leading experts in a broad range of protein-related topics.