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A new sequence alignment algorithm based on hybrid intelligence algorithm

Junen Guo, Huanlong Zhang

Bioinformatics is the subject of using computer to store, retrieve and analyze biological information. Sequence alignment is a basic problemin Bioinformatics, and itsmain researchwork is to develop rapid and effective sequence alignment algorithms. We may discover functional, structural and evolutionary information in biological sequences by sequence comparing. The ant colony optimization genetic algorithm(ACOGA) is an improved algorithmbased on theACOby optimizing its parameters through the GA. In this paper, the ACOGA is applied to sequence alignment in bioinformatics and a novel Hybrid Intelligence Algorithm is proposed. The experiment results indicate that the newly proposed algorithm is effective