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Family Competition Pheromone Genetic Algorithm for Comparative Genome Assembly

Family Competition Pheromone Genetic Algorithm for Comparative Genome Assembly
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摘要 Genome assembly is a prerequisite step for analyzing next generation sequencing data and also far from being solved. Many assembly tools have been proposed and used extensively. Majority of them aim to assemble sequencing reads into contigs; however, we focus on the assembly of contigs into scaffolds in this paper. This is called scaffolding, which estimates the relative order of the contigs as well as the size of the gaps between these contigs. Pheromone trail-based genetic algorithm (PGA) was previously proposed and had decent performance according to their paper. From our previous study, we found that family competition mechanism in genetic algorithm is able to further improve the results. Therefore, we propose family competition pheromone genetic algorithm (FCPGA) and demonstrate the improvement over PGA. Genome assembly is a prerequisite step for analyzing next generation sequencing data and also far from being solved. Many assembly tools have been proposed and used extensively. Majority of them aim to assemble sequencing reads into contigs; however, we focus on the assembly of contigs into scaffolds in this paper. This is called scaffolding, which estimates the relative order of the contigs as well as the size of the gaps between these contigs. Pheromone trail-based genetic algorithm (PGA) was previously proposed and had decent performance according to their paper. From our previous study, we found that family competition mechanism in genetic algorithm is able to further improve the results. Therefore, we propose family competition pheromone genetic algorithm (FCPGA) and demonstrate the improvement over PGA.
出处 《Journal of Electronic Science and Technology》 CAS 2014年第4期405-409,共5页 电子科技学刊(英文版)
关键词 Genetic algorithm genome typing next generation sequencing. Genetic algorithm, genome typing,next generation sequencing.
作者简介 C.-H. Su is with the Biodiversity Research Center, Academia Sinica, Taipei (e-mail: chienhao@gmail.com).Center for Research, Diagnostics and Vaccine Development, Centers for Disease Control, Taichung (e-mail: nipmcsc@cdc.gov.tw).C.-Y. Kao is with the Department of Computer Science and Information Engineering, National Taiwan University, Taipei (e-mail: cykao@csie.ntu.edu.tw).H.-T. Chu is with the Department of Computer Science and Information Engineering, Asia University, Taichung (Corresponding author: e-mail: htchu@asia.edu.tw).
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