GWOMF: Grey Wolf Optimization for motif finding

Abstract

The DNA motif discovery is an important step to study gene function. A DNA motif refers to a short similar repeated pattern of nucleotides that has biological meaning. In this paper, a bio-inspired algorithm called Grey Wolf Optimizer technique for DNA motif finding (GWOMF) is presented and evaluated on six synthetic datasets. Experimental results show that the GWOMF algorithm is more efficient than the state-of-art methods with a comparable computational time. Results confirmed the robustness of the new technique and demonstrate its value as a motif discovery tool with average success rate of 86.6%.