• DocumentCode
    1841367
  • Title

    A Genetic Algorithm for Single Individual SNP Haplotype Assembly

  • Author

    Wu, Jingli ; Wang, Jianxin ; Chen, Jian´er

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    1012
  • Lastpage
    1017
  • Abstract
    The minimum error correction (MEC) model is one of the widely accepted computational model for single individual haplotype reconstruction problem, and it has been proved to be NP-complete by Lippert et al.. Qian et al. presented a particle swarm optimization (PSO) algorithm to solve the model, and the length of a particle code is equal to the number of fragments. However, there are hundreds and thousands of fragments in practical applications, the PSO algorithm based on this kind of long particle code can not obtain high reconstruction rate efficiently. In this paper, a practical heuristic algorithm based on genetic algorithm (GA) is presented to solve the problem. A kind of short chromosome code and an effective climb operator are designed for the algorithm. Experimental results indicate that the algorithm designed in this paper can get higher reconstruction rate than the PSO algorithm.
  • Keywords
    computational complexity; error correction; genetic algorithms; NP-complete; genetic algorithm; minimum error correction model; particle swarm optimization algorithm; practical heuristic algorithm; single individual SNP haplotype assembly; Algorithm design and analysis; Assembly; Bioinformatics; Biological cells; Clustering algorithms; Computational modeling; Error correction; Genetic algorithms; Genomics; Heuristic algorithms; Single nucleotide polymorphisms; climb operator; genetic algorithm; haplotype; the minimum error correction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.95
  • Filename
    4709113