Bacterial Foraging Optimization Algorithm Integrating Tabu Search for Motif Discovery

摘要

Extracting motifs in the sea of DNA sequences is an intricate task but have great significance. We propose an alternative solution integrating bacterial foraging optimization (BFO) algorithm and Tabu Search (TS) algorithm namely TS-BFO. We modify the original BFO via established a self-control multi-length chemotactic step mechanism, and introduce Rao metric. The experiments on real data set extracted from TRANSFAC and SCPD database have predicted meaningful motif which demonstrated that TS BFO is a promising approach for motif discovery.