Harris Hawks Optimizer for Solving Multiple Sequence Alignment

Abstract

In the field of bioinformatics, sequence alignment is crucial for the genes study and drug development. Multiple Sequence Alignment (MSA) is an NP-hard problem in the sequence alignment. In the last three decades, the MSA problem has drawn a great deal of interest from biologists and scientists. It is an essential method to identify the structural and behavioural attributes of biomolecules present in organisms and vital to biological processes. Nature-inspired algorithms are one of the approaches to solve the MSA problem of aligning multiple sequences at a time. They construct powerful tools to overpower traditional optimization techniques to find an accurate solution. This investigative work (HHO-MSA) brings a new nature-inspired algorithm known as the Harris Hawks Optimizer (HHO) Algorithm to solve the MSA problem. HHO’s key influence is the cooperative behaviour and hunting style of the Harris hawks in nature called the surprise pounce. The computational results across five references of the BAliBASE dataset proven the proposed HHO-MSA method’s effectiveness by reaching great results (up to 83.5% optimum solutions). Findings were statistically supported while comparing it with other established literature works to solve the MSA problem.