Improved short adjacent repeat identification using three evolutionary Monte Carlo schemes Online publication date: Mon, 20-Oct-2014
by Jin Xu; Qiwei Li; Victor O.K. Li; Shuo-Yen Robert Li; Xiaodan Fan
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 8, No. 4, 2013
Abstract: This paper employs three Evolutionary Monte Carlo (EMC) schemes to solve the Short Adjacent Repeat Identification Problem (SARIP), which aims to identify the common repeat units shared by multiple sequences. The three EMC schemes, i.e., Random Exchange (RE), Best Exchange (BE), and crossover are implemented on a parallel platform. The simulation results show that compared with the conventional Markov Chain Monte Carlo (MCMC) algorithm, all three EMC schemes can not only shorten the computation time via speeding up the convergence but also improve the solution quality in difficult cases. Moreover, we observe that the performances of different EMC schemes depend on the degeneracy degree of the motif pattern.
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