G. F. D. Zafalon, E. A. Marucci, J. C. Momente, J. Amazonas, L. Sato, J. M. Machado
{"title":"Improvements in the score matrix calculation method using parallel score estimating algorithm","authors":"G. F. D. Zafalon, E. A. Marucci, J. C. Momente, J. Amazonas, L. Sato, J. M. Machado","doi":"10.4236/JBPC.2013.42006","DOIUrl":null,"url":null,"abstract":"The \nincreasing amount of sequences stored in genomic databases has become unfeasible \nto the sequential analysis. Then, the parallel computing brought its power to \nthe Bioinformatics through parallel algorithms to align and analyze the \nsequences, providing improvements mainly in the running time of these \nalgorithms. In many situations, the parallel strategy contributes to reducing \nthe computational complexity of the big problems. This work shows some results \nobtained by an implementation of a parallel score estimating technique for \nthe score matrix calculation stage, which is the first stage of a progressive \nmultiple sequence alignment. The performance and quality of the parallel \nscore estimating are compared with the results of a dynamic programming \napproach also implemented in parallel. This comparison shows a significant reduction \nof running time. Moreover, the quality of the \nfinal alignment, using the new strategy, is analyzed and compared with \nthe quality of the approach with dynamic programming.","PeriodicalId":62927,"journal":{"name":"生物物理化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"生物物理化学(英文)","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.4236/JBPC.2013.42006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The
increasing amount of sequences stored in genomic databases has become unfeasible
to the sequential analysis. Then, the parallel computing brought its power to
the Bioinformatics through parallel algorithms to align and analyze the
sequences, providing improvements mainly in the running time of these
algorithms. In many situations, the parallel strategy contributes to reducing
the computational complexity of the big problems. This work shows some results
obtained by an implementation of a parallel score estimating technique for
the score matrix calculation stage, which is the first stage of a progressive
multiple sequence alignment. The performance and quality of the parallel
score estimating are compared with the results of a dynamic programming
approach also implemented in parallel. This comparison shows a significant reduction
of running time. Moreover, the quality of the
final alignment, using the new strategy, is analyzed and compared with
the quality of the approach with dynamic programming.