An improved scoring matrix for multiple sequence alignment
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 ad...
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sg-ntu-dr.10356-1013752023-03-04T17:19:06Z An improved scoring matrix for multiple sequence alignment Shu, Jian-Jun Yong, Kian Yan Chan, Weng Kong School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mathematics and analysis 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 multiple sequence alignment. Alignments with equal scores are iteratively rescored with the joint weight matrix of increasing level (nucleotide pairs, triplets, and so on) until one single best alignment is eventually found. This method for resolving ambiguity in multiple sequence alignment can be easily implemented by use of the improved scoring matrix. Published version 2014-01-21T07:00:24Z 2019-12-06T20:37:26Z 2014-01-21T07:00:24Z 2019-12-06T20:37:26Z 2012 2012 Journal Article Shu, J. J., Yong, K. Y., & Chan, W. K. (2012). An improved scoring matrix for multiple sequence alignment. Mathematical problems in engineering, 2012-490649. https://hdl.handle.net/10356/101375 http://hdl.handle.net/10220/18649 10.1155/2012/490649 162023 en Mathematical problems in engineering © 2012 The Author(s). This paper was published in Mathematical Problems in Engineering and is made available as an electronic reprint (preprint) with permission of The Author(s).The paper can be found at the following official DOI: [http://dx.doi.org/10.1155/2012/490649]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf |
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DRNTU::Engineering::Mathematics and analysis Shu, Jian-Jun Yong, Kian Yan Chan, Weng Kong An improved scoring matrix for multiple sequence alignment |
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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 multiple sequence alignment. Alignments with equal scores are iteratively rescored with the joint weight matrix of increasing level (nucleotide pairs, triplets, and so on) until one single best alignment is eventually found. This method for resolving ambiguity in multiple sequence alignment can be easily implemented by use of the improved scoring matrix. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Shu, Jian-Jun Yong, Kian Yan Chan, Weng Kong |
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Article |
author |
Shu, Jian-Jun Yong, Kian Yan Chan, Weng Kong |
author_sort |
Shu, Jian-Jun |
title |
An improved scoring matrix for multiple sequence alignment |
title_short |
An improved scoring matrix for multiple sequence alignment |
title_full |
An improved scoring matrix for multiple sequence alignment |
title_fullStr |
An improved scoring matrix for multiple sequence alignment |
title_full_unstemmed |
An improved scoring matrix for multiple sequence alignment |
title_sort |
improved scoring matrix for multiple sequence alignment |
publishDate |
2014 |
url |
https://hdl.handle.net/10356/101375 http://hdl.handle.net/10220/18649 |
_version_ |
1759856487694336000 |