Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases

Authors:
Arpad Kelemen;Athanasios V. Vasilakos;Yulan Liang
Affiliations:
Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, MD;Department of Computer and Telecommunications Engineering, University of Western Macedonia, Kozani, Greece;Department of Family and Community Health, University of Maryland, Baltimore, MD
Venue:
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Year:
2009

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Abstract

Comprehensive evaluation of common genetic variations through association of single-nucleotide polymorphism (SNP) structure with common complex disease in the genome-wide scale is currently a hot area in human genome research due to the recent development of the Human Genome Project and HapMap Project. Computational science, which includes computational intelligence (CI), has recently become the third method of scientific enquiry besides theory and experimentation. There have been fast growing interests in developing and applying CI in diseasemapping using SNP and haplotype data. Some of the recent studies have demonstrated the promise and importance of CI for common complex diseases in genomic association study using SNP/haplotype data, especially for tackling challenges, such as gene-gene and gene-environment interactions, and the notorious "curse of dimensionality" problem. This review provides coverage of recent developments of CI approaches for complex diseases in genetic association study with SNP/haplotype data.