title: An Improved Position Weight Matrix method based on an entropy measure for the recognition of prokaryotic promoters.
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.
authors.affiliation: School of Electronics and Information Engineering, Soochow University, Suzhou, Jiangsu, 215021, China. suzhouqinqin@gmail.com
authors.forename: Qinqin
authors.initials: Q
authors.lastname: Wu
authors.forename: Jiajun
authors.initials: J
authors.lastname: Wang
authors.forename: Hong
authors.initials: H
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000235:genetics*; D001483:Base Sequence; D030541:Databases, Genetic; D019277:Entropy; D056510:Position-Specific Scoring Matrices; D011387:Prokaryotic Cells; D011401:Promoter Regions, Genetic