Arakil Chentoufi, Abdelhakim El Fatmi, M. A. Bekri, Said Benhlima, M. Sabbane
{"title":"A heuristic method based on multi-objective optimization concept for solving RNA multiple alignment","authors":"Arakil Chentoufi, Abdelhakim El Fatmi, M. A. Bekri, Said Benhlima, M. Sabbane","doi":"10.15866/ireaco.v10i5.12395","DOIUrl":null,"url":null,"abstract":"Multiple sequence alignment (MSA) is an NP-complete and important problem in Bioinformatics. For this reason, a number of computational approaches have been developed to achieve the optimal alignment. However, this goal remains a big challenge. MSA can be also treated as a multi-objective optimization problem. In the same way, we present a new method using Pareto Front and Genetic Algorithm (GA), called MOO-RNA, to align a set of RNA sequences. We validate our method on a set of alignments of Bralibase II. The results show that the quality of our method, in terms of Sum-of-Pairs Score (SPS) and Structure Conservation Index (SCI), is improved.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"10 1","pages":"371"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Automatic Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15866/ireaco.v10i5.12395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
Multiple sequence alignment (MSA) is an NP-complete and important problem in Bioinformatics. For this reason, a number of computational approaches have been developed to achieve the optimal alignment. However, this goal remains a big challenge. MSA can be also treated as a multi-objective optimization problem. In the same way, we present a new method using Pareto Front and Genetic Algorithm (GA), called MOO-RNA, to align a set of RNA sequences. We validate our method on a set of alignments of Bralibase II. The results show that the quality of our method, in terms of Sum-of-Pairs Score (SPS) and Structure Conservation Index (SCI), is improved.