基于遗传算法的多序列比对优化方法

A. Mishra, Dr. Brijesh Kumar Tripathi, Sudhir Singh Soam
{"title":"基于遗传算法的多序列比对优化方法","authors":"A. Mishra, Dr. Brijesh Kumar Tripathi, Sudhir Singh Soam","doi":"10.1109/ComPE49325.2020.9200060","DOIUrl":null,"url":null,"abstract":"Multiple sequence alignment (MSA) is an elementary task of bioinformatics where the alignment of three or more biological sequences is produced in a way that helps to identify the homologous regions in the sequences. This research paper proposes a genetic algorithm-based optimization approach that can enhance the value of multiple sequence alignment (MSA) generated by the progressive technique. Mutation operators like gap insertion mutation and gap removal mutations are applied to enhance the value of the MSA obtained by the progressive technique of alignment.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"9 1","pages":"415-418"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Genetic Algorithm based Approach for the Optimization of Multiple Sequence Alignment\",\"authors\":\"A. Mishra, Dr. Brijesh Kumar Tripathi, Sudhir Singh Soam\",\"doi\":\"10.1109/ComPE49325.2020.9200060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple sequence alignment (MSA) is an elementary task of bioinformatics where the alignment of three or more biological sequences is produced in a way that helps to identify the homologous regions in the sequences. This research paper proposes a genetic algorithm-based optimization approach that can enhance the value of multiple sequence alignment (MSA) generated by the progressive technique. Mutation operators like gap insertion mutation and gap removal mutations are applied to enhance the value of the MSA obtained by the progressive technique of alignment.\",\"PeriodicalId\":6804,\"journal\":{\"name\":\"2020 International Conference on Computational Performance Evaluation (ComPE)\",\"volume\":\"9 1\",\"pages\":\"415-418\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computational Performance Evaluation (ComPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ComPE49325.2020.9200060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computational Performance Evaluation (ComPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComPE49325.2020.9200060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

多序列比对(MSA)是生物信息学的一项基本任务,其中三个或多个生物序列的比对有助于识别序列中的同源区域。本文提出了一种基于遗传算法的优化方法,该方法可以提高渐进式技术生成的多序列比对(MSA)值。利用间隙插入突变和间隙移除突变等突变算子,提高了渐进式比对技术得到的MSA值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Genetic Algorithm based Approach for the Optimization of Multiple Sequence Alignment
Multiple sequence alignment (MSA) is an elementary task of bioinformatics where the alignment of three or more biological sequences is produced in a way that helps to identify the homologous regions in the sequences. This research paper proposes a genetic algorithm-based optimization approach that can enhance the value of multiple sequence alignment (MSA) generated by the progressive technique. Mutation operators like gap insertion mutation and gap removal mutations are applied to enhance the value of the MSA obtained by the progressive technique of alignment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信