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Lecture notes in computer science : multiple DNA sequence alignment using joint weight matrix

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Lecture notes in computer science : multiple DNA sequence alignment using joint weight matrix

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Title: Lecture notes in computer science : multiple DNA sequence alignment using joint weight matrix
Author: Shu, Jian Jun; Yong, Kian Yan; Chan, Weng Kong
Copyright year: 2011
Abstract: The way for performing multiple sequence alignment is based on the criterion of the maximum scored information content computed from a weight matrix, but it is possible to have two or more alignments to have the same highest score leading to ambiguities in selecting the best alignment. This paper addresses this issue by introducing the concept of joint weight matrix to eliminate the randomness in selecting the best alignment of multiple sequences. Alignments with equal scores are iteratively re-scored with joint weight matrix of increasing level (nucleotide pairs, triplets and so on) until one single best alignment is eventually found. This method can be easily implemented to algorithms using weight matrix for scoring such as those based on the widely used Gibbs sampling method.
Subject: DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Type: Conference Paper
Conference name: International Conference on Computational Science and Its Applications (11th : 2011 : Santander, Spain)
School: School of Mechanical and Aerospace Engineering
Rights: © 2011 Springer-Verlag Berlin Heidelberg. This is the author created version of a work that has been peer reviewed and accepted for publication by Computational Science and Its Applications - ICCSA 2011, Springer-Verlag Berlin Heidelberg. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.1007/978-3-642-21931-3_51].
Version: Accepted version

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