Knowledge and Systems Engineering, International Conference on (2011)
Oct. 14, 2011 to Oct. 17, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/KSE.2011.27
Haplotype inference is a challenging computational problem in population genetics. We introduce an approach using Ant Colony Optimization (ACO) metaheuristic, named ACOHAP, to infer haplotypes from unphased Single Polymorphism Nucleotide (SNP) marker data. Our method employs an efficient method for constructing the ACO graph through which ants flexibly traverse to build haplotypes. ACOHAP also uses a well-performed pheromone trail update strategy and a local search to improve the performance. Experiments showed that ACOHAP outperformed the state-of-the-art methods for haplotype inference in both simulated and biological data.
Ant Colony Optimization, Haplotype inference, ACOHAP
D. D. Duc and H. H. Xuan, "A Fast and Efficient Ant Colony Optimization for Haplotype Inference by Pure Parsimony," Knowledge and Systems Engineering, International Conference on(KSE), Hanoi, Vietnam, 2011, pp. 128-134.