A memetic particle swarm optimization algorithm for solving the DNA fragment assembly problem

Ko Wei Huang, Jui Le Chen, Chu Sing Yang, Chun Wei Tsai

研究成果: Article同行評審

20 引文 斯高帕斯(Scopus)

摘要

Determining the sequence of a long DNA chain first requires dividing it into subset fragments. The DNA fragment assembly (DFA) approach is then used for reassembling the fragments as an NP-hard problem that is the focus of increasing attention from combinatorial optimization researchers within the computational biology community. Particle swarm optimization (PSO) is one of the most important swarm intelligence meta-heuristic optimization techniques to solve NP-hard combinatorial optimization problems. This paper proposes a memetic PSO algorithm based on two initialization operators and the local search operator for solving the DFA problem by following the overlap–layout–consensus model to maximize the overlapping score measurement. The results, based on 19 coverage DNA fragment datasets, indicate that the PSO algorithm combining tabu search and simulated annealing-based variable neighborhood search local search can achieve the best overlap scores.

原文English
頁(從 - 到)495-506
頁數12
期刊Neural Computing and Applications
26
發行號3
DOIs
出版狀態Published - 2015 四月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 人工智慧

指紋

深入研究「A memetic particle swarm optimization algorithm for solving the DNA fragment assembly problem」主題。共同形成了獨特的指紋。

引用此