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Computational Biology and Chemistry
Volume 29, Issue 2, April 2005, Pages 175-181
 
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doi:10.1016/j.compbiolchem.2004.12.005    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2004 Published by Elsevier Ltd.

Software note

MSAID: multiple sequence alignment based on a measure of information discrepancy

Min Zhanga, c, Corresponding Author Contact Information, E-mail The Corresponding Author, Weiwu Fangb, Junhua Zhangb and Zhongxian Chia

aDepartment of Computer Science and Engineering, Dalian University of Technology, Dalian 116024, China bAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China cCollege of Information Engineering, Dalian University, Dalian 116622, China

Received 22 June 2004; 
revised 10 December 2004; 
accepted 10 December 2004. 
Available online 12 April 2005.

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Abstract

We propose an algorithm of global multiple sequence alignment that is based on a measure of what we call information discrepancy. The algorithm follows a progressive alignment iteration strategy that makes use of what we call a function of degree of disagreement (FDOD). MSAID begins with distance calculation of pairwise sequences, based on FDOD as a numerical scoring measure. In the next step, the resulting distance matrix is used to construct a guide tree via the neighbor-joining method. The tree is then used to produce a multiple alignment. Current alignment is next used to produce a new matrix and a new tree (with FDOD scoring measure again). This iterative process continues until convergence criteria (or a stopping rule) are satisfied. MSAID was tested and compared with other prior methods by using reference alignments from BAliBASE 2.01. For the alignments with no large N/C-terminal extensions or internal insertions MSAID received the top overall average in the tests. Moreover, the results of testing indicate that MSAID performs as well as other alignment methods with an occasional tendency to perform better than these prior techniques. We, therefore, believe that MSAID is a solid and reliable method of choice, which is often (if not always) superior to other global alignment techniques.

Keywords: Multiple sequence alignment; Progressive alignment; Iterative strategy; FDOD measure

Article Outline

1. Introduction
2. MSAID algorithm
2.1. Complete information set and FDOD
2.2. Multiple sequence alignment algorithm MSAID
3. Materials, compared methods and statistical analysis
4. Results
4.1. Comparing MSAID with other iteratively progressive multiple sequence alignment methods
4.2. Comparing MSAID with other multiple sequence alignment methods
4.3. Effect of FDOD measure
5. Application to 1r69
6. Conclusion
Acknowledgements
References


 
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