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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/27764

Title: Multiple Sequence Alignment for Functional Correlation among Low Similarity Sequences
Authors: Wei-Yao Chou;Wei-I Chou;Tun-Wen Pai;Shu-Chuan Lin;Fan-Yu Chang;Yuh-Ju Sun;Chuan-Yi Tang;Margaret Dah-Tsyr Chang
Contributors: NTOU:Department of Computer Science and Engineering
Date: 2008
Issue Date: 2011-10-21T02:33:56Z
Publisher: Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008)
Abstract: Abstract:Multiple sequence alignment is a broadly used methodology in biological applications. It is expected to locate consensus sequence stretches with evolutionary and functional conservation. However, when sequence similarity among the queries becomes low, it works poorly. The aim of this study is to incorporate important biological knowledge and assumption to improve the quality of a general alignment on low similarity sequences such as carbohydrate binding module (CBM) families. Since the recognition of characteristic patterns in CBMs does not apply to a general model, a more accurate scoring function employing secondary-structure-based and key-residue-weighted algorithms for alignment was designed to approach this goal. Our results indicated that the new method was practically applicable to identify the key residues in terms of three-dimensional structures, while conventional tools could fail.. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1
Relation: pp.115-125
URI: http://ntour.ntou.edu.tw/handle/987654321/27764
Appears in Collections:[資訊工程學系] 演講及研討會

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