An Improved Position Weight Matrix method based on an entropy measure for the recognition of prokaryotic promoters Online publication date: Sat, 24-Jan-2015
by Qinqin Wu, Jiajun Wang, Hong Yan
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 5, No. 1, 2011
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.
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