{"title":"Phylogenetic analysis using Bayesian model","authors":"W. Lu, Michael S. Hanrahan","doi":"10.1109/ASEEZONE1.2014.6820677","DOIUrl":null,"url":null,"abstract":"Bayesian inference has been widely applied for phylogenetic and phyloinformatic analysis in recent years. In this paper we build up a high performance computing platform using OpenMPI with free-cost open source Ubuntu Linux operating systems, and then apply the Bayesian inference model to construct a phylogenetic tree of various biological species based on similarities and differences in their physical and genetic characteristics. A case study is also conducted and the experimental evaluation results to show that our cluster platform has achieved a good performance in the terms of time complexity when analyzing the molecular data using Bayesian model, leading a pilot inter-disciplinary Bioinformatics education program in between Computer Science and Biology.","PeriodicalId":353468,"journal":{"name":"Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASEEZONE1.2014.6820677","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Bayesian inference has been widely applied for phylogenetic and phyloinformatic analysis in recent years. In this paper we build up a high performance computing platform using OpenMPI with free-cost open source Ubuntu Linux operating systems, and then apply the Bayesian inference model to construct a phylogenetic tree of various biological species based on similarities and differences in their physical and genetic characteristics. A case study is also conducted and the experimental evaluation results to show that our cluster platform has achieved a good performance in the terms of time complexity when analyzing the molecular data using Bayesian model, leading a pilot inter-disciplinary Bioinformatics education program in between Computer Science and Biology.