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    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/97013
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/97013


    Title: TCS: A New Multiple Sequence Alignment Reliability Measure to Estimate Alignment Accuracy and Improve Phylogenetic Tree Reconstruction
    Authors: 張家銘
    Chang, Jia-Ming;Tommaso, Paolo Di;Notredame, Cedric
    Contributors: 資科系
    Keywords: T-Coffee;multiple sequence alignment;alignment uncertainty;alignment confidence;phylogeny;homology modeling
    Date: 2014-06
    Issue Date: 2016-05-30 17:24:17 (UTC+8)
    Abstract: Multiple sequence alignment (MSA) is a key modeling procedure when analyzing biological sequences. Homology and evolutionary modeling are the most common applications of MSAs. Both are known to be sensitive to the underlying MSA accuracy. In this work, we show how this problem can be partly overcome using the transitive consistency score (TCS), an extended version of the T-Coffee scoring scheme. Using this local evaluation function, we show that one can identify the most reliable portions of an MSA, as judged from BAliBASE and PREFAB structure-based reference alignments. We also show how this measure can be used to improve phylogenetic tree reconstruction using both an established simulated data set and a novel empirical yeast data set. For this purpose, we describe a novel lossless alternative to site filtering that involves overweighting the trustworthy columns. Our approach relies on the T-Coffee framework; it uses libraries of pairwise alignments to evaluate any third party MSA. Pairwise projections can be produced using fast or slow methods, thus allowing a trade-off between speed and accuracy. We compared TCS with Heads-or-Tails, GUIDANCE, Gblocks, and trimAl and found it to lead to significantly better estimates of structural accuracy and more accurate phylogenetic trees. The software is available from www.tcoffee.org/Projects/tcs.
    Relation: Molecular Biology and Evolution, Vol.31, No.6, pp.1625-37
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1093/molbev/msu117
    DOI: 10.1093/molbev/msu117
    Appears in Collections:[資訊科學系] 期刊論文

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