Multipopulation harmony search algorithm for the detection of high-order SNP interactions | Zendy

Shouheng Tuo | Zendy; Haiyan Liu | Zendy; Hao Chen | Zendy

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Multipopulation harmony search algorithm for the detection of high-order SNP interactions

Author(s) -

Shouheng Tuo,

Haiyan Liu,

Hao Chen

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa215

Subject(s) - snp , computer science , harmony search , algorithm , artificial intelligence , pattern recognition (psychology) , single nucleotide polymorphism , biology , genotype , genetics , gene

Recently, multiobjective swarm intelligence optimization (SIO) algorithms have attracted considerable attention as disease model-free methods for detecting high-order single nucleotide polymorphism (SNP) interactions. However, a strict Pareto optimal set may filter out some of the SNP combinations associated with disease status. Furthermore, the lack of heuristic factors for finding SNP interactions and the preference for discrimination approaches to disease models are considerable challenges for SIO.

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