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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/86640
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/86640


    Title: Improving the Alignment Quality of Consistency Based Aligners with an Evaluation Function Using Synonymous Protein Words
    Authors: Lin, Hsin-Nan;Notredame, Cédric;Chang, Jia-Ming;Sung, Ting-Yi;Hsu, Wen-Lian
    張家銘
    Contributors: 資科系
    Date: 2011
    Issue Date: 2016-04-27 15:30:13 (UTC+8)
    Abstract: Most sequence alignment tools can successfully align protein sequences with higher levels of sequence identity. The accuracy of corresponding structure alignment, however, decreases rapidly when considering distantly related sequences (<20% identity). In this range of identity, alignments optimized so as to maximize sequence similarity are often inaccurate from a structural point of view. Over the last two decades, most multiple protein aligners have been optimized for their capacity to reproduce structure-based alignments while using sequence information. Methods currently available differ essentially in the similarity measurement between aligned residues using substitution matrices, Fourier transform, sophisticated profile-profile functions, or consistency-based approaches, more recently.In this paper, we present a flexible similarity measure for residue pairs to improve the quality of protein sequence alignment. Our approach, called SymAlign, relies on the identification of conserved words found across a sizeable fraction of the considered dataset, and supported by evolutionary analysis. These words are then used to define a position specific substitution matrix that better reflects the biological significance of local similarity. The experiment results show that the SymAlign scoring scheme can be incorporated within T-Coffee to improve sequence alignment accuracy. We also demonstrate that SymAlign is less sensitive to the presence of structurally non-similar proteins. In the analysis of the relationship between sequence identity and structure similarity, SymAlign can better differentiate structurally similar proteins from non- similar proteins. We show that protein sequence alignments can be significantly improved using a similarity estimation based on weighted n-grams. In our analysis of the alignments thus produced, sequence conservation becomes a better indicator of structural similarity. SymAlign also provides alignment visualization that can display sub-optimal alignments on dot-matrices. The visualization makes it easy to identify well-supported alternative alignments that may not have been identified by dynamic programming. SymAlign is available at http://bio-cluster.iis.sinica.edu.tw/SymAlign/.
    Relation: PLoS One, 6(12), e27872
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1371/journal.pone.0027872
    DOI: 10.1371/journal.pone.0027872
    Appears in Collections:[資訊科學系] 期刊論文

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