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A Particle Swarm Optimization Algorithm Based on Optimal Result Set for Haplotyping a Single Individual
May 27-May 30
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/BMEI.2008.1202008 International Conference on BioM ...
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In this paper, a practical algorithm PS-MEC is presented based on the idea of generating a small set of optimal results to reduce the probability of losing the best result. We design a kind of short particle code for the algorithm by taking advantage of the low heterozygous frequency of single nucleotide polymorphisms. Experimental results indicate PS-MEC can get a set containing no more than four results in general, and which contains at least a pair of haplotypes that has higher reconstruction rate than those generated by previous algorithms solving the model. Moreover, PS-MEC is still efficient even for solving large size problems.
Citation:
Jingli Wu, Jianxin Wang, Jian?er Chen, "A Particle Swarm Optimization Algorithm Based on Optimal Result Set for Haplotyping a Single Individual," bmei, vol. 1, pp.395-399, 2008 International Conference on BioMedical Engineering and Informatics, 2008
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