Abstract

In this paper, an artificial bee colony (ABC) algorithm for the multiple sequence alignment (MSA) problem has been proposed. The ABC algorithm is a novel optimization approach inspired by a particular intelligent behaviour of honey bee swarms. Taken the discreteness of the MSA problem into consideration, a new method of ABC algorithm for determining a food source in the neighbourhood is introduced. The performance of our ABC approach is compared with other commonly used algorithms for MSA. Computational results demonstrate the superiority of the new ABC algorithm over genetic algorithm (GA) and particle swarm optimization (PSO) for many sequences with different length and identity. The new approach is more robust and obtains better mathematical and biological quality.

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