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Corrigendum for Hsu et al., Nucl. Acids Res. 34 (Web Server issue) W356-W361.

Nucleic Acids Research Advance Access originally published online on January 4, 2008
Nucleic Acids Research 2008 36(4):1400-1406; doi:10.1093/nar/gkm717
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Nucleic Acids Research, 2008, Vol. 36, No. 4 1400-1406
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corrigendum

Corrigendum

 

MAGIIC-PRO: detecting functional signatures by efficient discovery of long patterns in protein sequences

Chen-Ming Hsu, Chien-Yu Chen1,* and Baw-Jhiune Liu

Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, 320, Taiwan, Republic of China and 1Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, Taipei, 106, Taiwan, Republic of China

*To whom correspondence should be addressed. Tel: +886 2 33665334; Fax: +886 2 23627620; Email: cychen{at}mars.csie.ntu.edu.tw

Received February 14, 2006. Revised March 2, 2006. Accepted April 11, 2006.

ABSTRACT

This paper presents a web service named MAGIIC-PRO, which aims to discover functional signatures of a query protein by sequential pattern mining. Automatic discovery of patterns from unaligned biological sequences is an important problem in molecular biology. MAGIIC-PRO is different from several previously established methods performing similar tasks in two major ways. The first remarkable feature of MAGIIC-PRO is its efficiency in delivering long patterns. With incorporating a new type of gap constraints and some of the state-of-the art data mining techniques, MAGIIC-PRO usually identifies satisfied patterns within an acceptable response time. The efficiency of MAGIIC-PRO enables the users to quickly discover functional signatures of which the residues are not from only one region of the protein sequences or are only conserved in few members of a protein family. The second remarkable feature of MAGIIC-PRO is its effort in refining the mining results. Considering large flexible gaps improves the completeness of the derived functional signatures. The users can be directly guided to the patterns with as many blocks as that are conserved simultaneously. In this paper, we show by experiments that MAGIIC-PRO is efficient and effective in identifying ligand-binding sites and hot regions in protein–protein interactions directly from sequences. The web service is available at http://biominer.bime.ntu.edu.tw/magiicpro and a mirror site at http://biominer.cse.yzu.edu.tw/magiicpro.


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