Application with a hybrid ant colony optimisation in motif detecting problem
by Yi Zhang; Meng Zhang; Zhili Pei
International Journal of Computer Applications in Technology (IJCAT), Vol. 44, No. 2, 2012

Abstract: In this paper, a hybrid optimisation algorithm for the motif detection problem of biological sequences is presented. Our method is improved Gibbs sampling method by employing an improved ant colony optimisation (ACO) algorithm. The goal of our method is to reduce the required computing time and get better solution. First, we find a set of better candidate positions for revising the motif by using an improved ACO. Then we use these candidate positions as the input to the Gibbs sampling method. The simulation results show that by employing our improved algorithm, both efficiency and quality for detecting motifs are improved compared with simple Gibbs sampling method.

Online publication date: Thu, 23-Aug-2012

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