Title: An Improved Position Weight Matrix method based on an entropy measure for the recognition of prokaryotic promoters

Authors: Qinqin Wu, Jiajun Wang, Hong Yan

Addresses: School of Electronics and Information Engineering, Soochow University, Suzhou, Jiangsu, 215021, China; and Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. ' School of Electronics and Information Engineering, Soochow University, Suzhou, Jiangsu, 215021, China. ' Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong; School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia

Abstract: In this paper, an Improved Position Weight Matrix (IPWM) method is proposed based on an entropy measure for the recognition of prokaryotic promoters. In this method, the conservative sites of the prokaryotic promoters are extracted according to an entropy measure, and then two improved position weight matrices are constructed based on the training set. By using the values of the matrix elements in the specific columns corresponding to the extracted conservative sites, the test sequences are scored and subsequently classified. Experiment results on several datasets show that the proposed algorithm outperforms the existing ones.

Keywords: prokaryotic promoters; prokaryotic promoter recognition; conservative sites; information entropy; PWM; position weight matrix; entropy measures.

DOI: 10.1504/IJDMB.2011.038575

International Journal of Data Mining and Bioinformatics, 2011 Vol.5 No.1, pp.22 - 37

Received: 08 Dec 2008
Accepted: 30 May 2009
Published online: 24 Jan 2015 *

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