{"title":"A Classification Method for RNA Splicing Regulatory Elements","authors":"Meng Ma, Yang Wang, Ying Ru, Zefeng Wang","doi":"10.3969/J.ISSN.0258-8021.2012.01.008","DOIUrl":null,"url":null,"abstract":"The sequence classification methods have broad application in various bioinformatics areas such as the identification of regulatory elements of transcription and the prediction of protein structure.Here we presented a new classification method to analyze short sequences based on their sequential features,and used this method to study RNA splicing regulatory elements.This method extracted the sequential features from the known spicing regulatory elements,and developed a scoring system to evaluate how possible a given short sequence can regulate RNA splicing.This method was compared with some other methods through applying to a set of exonic splicing enhancer(ESE) and silencer(ESS) octamers.The average prediction accuracy of this sequential feature-based method for three kinds of computation validation experiments reached about 93% and the transparent predictive structure of the method helps to interpret the biological mechanism.This paper shows a new method for biology series' data analysis and presents a new way for the study of regulatory sequences that control gene expression.","PeriodicalId":35998,"journal":{"name":"中国生物医学工程学报","volume":"14 1","pages":"45-52"},"PeriodicalIF":0.0000,"publicationDate":"2012-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国生物医学工程学报","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.3969/J.ISSN.0258-8021.2012.01.008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The sequence classification methods have broad application in various bioinformatics areas such as the identification of regulatory elements of transcription and the prediction of protein structure.Here we presented a new classification method to analyze short sequences based on their sequential features,and used this method to study RNA splicing regulatory elements.This method extracted the sequential features from the known spicing regulatory elements,and developed a scoring system to evaluate how possible a given short sequence can regulate RNA splicing.This method was compared with some other methods through applying to a set of exonic splicing enhancer(ESE) and silencer(ESS) octamers.The average prediction accuracy of this sequential feature-based method for three kinds of computation validation experiments reached about 93% and the transparent predictive structure of the method helps to interpret the biological mechanism.This paper shows a new method for biology series' data analysis and presents a new way for the study of regulatory sequences that control gene expression.
期刊介绍:
The mission of our journal: to be the bridge of the clinician, scientist and the industrial field, and to be the power of the development of biomedical engineering. The tenet of our journal: closely paying attention to and reporting the new theory, new means and new technology of biomedical engineering, tracking the newest applied achievement of biomedical engineering in clinic, serving vast clinicians, and promoting the developing of the subject of biomedical engineering. The feature of our journal: paying attention to the progress of science and technology, simultaneously, comprehensively weigh the relationship between the technology and one’s health in mind and body.