{"title":"A Modified Algorithm for Sequence Alignment Using Ant Colony System","authors":"A. Mikami, Jianming Shi","doi":"10.2197/IPSJTBIO.2.63","DOIUrl":null,"url":null,"abstract":"In this study, we use the Ant Colony System (ACS) to develop a heuristic algorithm for sequence alignment. This algorithm is certainly an improvement on ACS-MultiAlignment, which was proposed in 2005 for predicting major histocompatibility complex (MHC) class II binders. The numerical experiments indicate that this algorithm is as much as 2, 900 times faster than the original ACS-MultiAlignment algorithm. We also compare this algorithm to the other approaches such as Gibbs sampling algorithm using numerical experiments. The results show that our algorithm finds the best value prompter than Gibbs approach.","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":"2 1","pages":"63-73"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2197/IPSJTBIO.2.63","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPSJ Transactions on Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2197/IPSJTBIO.2.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 3
Abstract
In this study, we use the Ant Colony System (ACS) to develop a heuristic algorithm for sequence alignment. This algorithm is certainly an improvement on ACS-MultiAlignment, which was proposed in 2005 for predicting major histocompatibility complex (MHC) class II binders. The numerical experiments indicate that this algorithm is as much as 2, 900 times faster than the original ACS-MultiAlignment algorithm. We also compare this algorithm to the other approaches such as Gibbs sampling algorithm using numerical experiments. The results show that our algorithm finds the best value prompter than Gibbs approach.