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Bioinformatics Advance Access published online on July 26, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl398
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received November 14, 2005
Revised June 6, 2006
Accepted July 18, 2006

Article

ARCS: an aggregated related column scoring scheme for aligned sequences

Bin Song 1 #, Jeong-Hyeon Choi 2 #, Guangyu Chen 1, Jacek Szymanski 1, Guo-Qiang Zhang 1, Anthony K. H. Tung 3, Jaewoo Kang 4, Sun Kim 2, and Jiong Yang 1 *

1 Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, USA
2 School of Informatics, Indiana University, Bloomington, USA
3 Department of Computer Science, National University of Singapore, Singapore
4 Department of Computer Science, NC State University, Raleigh, USA

* To whom correspondence should be addressed.
Jiong Yang, E-mail: jiong.yang{at}case.edu


  Abstract

Motivation: Biologists frequently align multiple biological sequences to determine consensus sequences and/or search for predominant residues and conserved regions. Particularly, determining conserved regions in an alignment is one of the most important activities. Since protein sequences are often several-hundred residues or longer, it is difficult to distinguish biologically important conserved regions (motifs or domains) from others. The widely used tools, Logos, Al2co, Confind, and the entropy-based method, often fail to highlight such regions. Thus a computational tool that can highlight biologically important regions accurately will be highly desired.

Results: This paper presents a new scoring scheme ARCS (Aggregated Related Column Score) for aligned biological sequences. ARCS method considers not only the traditional character similarity measure but also column correlation. In an extensive experimental evaluation using 533 PROSITE patterns, ARCS is able to highlight the motif regions with up to 77.7% accuracy corresponding to the top 3 peaks.

Availability: The source code is available on http://bio.informatics.indiana.edu/projects/arcs.

Supplementary Material: http://bio.informatics.indiana.edu/projects/arcs.

Associate Editor: Christos Ouzounis

#These two authors contribute to the paper equally.


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