TFBS identification based on genetic algorithm with combined representations and adaptive post-processing
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AbstractMotivation: Identification of transcription factor binding sites (TFBSs) plays an important role in deciphering the mechanisms of gene regulation. Recently, GAME, a Genetic Algorithm (GA)-based approach with iterative post-processing, has shown superior performance in TFBS identification. However, the basic GA in GAME is not elaborately designed, and may be trapped in local optima in real problems. The feature operators are only applied in the post-processing, but the final performance heavily depends on the GA output. Hence, both effectiveness and efficiency of the overall algorithm can be improved by introducing more advanced representations and novel operators in the GA, as well as designing the post-processing in an adaptive way.
All Author(s) ListChan TM, Leung KS, Lee KH
Journal nameBioinformatics
Volume Number24
Issue Number3
Pages341 - 349
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesBiochemical Research Methods; BIOCHEMICAL RESEARCH METHODS; Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; BIOTECHNOLOGY & APPLIED MICROBIOLOGY; Computer Science; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; MATHEMATICAL & COMPUTATIONAL BIOLOGY; Mathematics; Statistics & Probability

Last updated on 2020-16-10 at 01:52