Computational Intelligence in Bioinformatics: SNP/Haplotype Data in Genetic Association Study for Common Diseases
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 Proje...
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Veröffentlicht in: | IEEE journal of biomedical and health informatics 2009-09, Vol.13 (5), p.841-847 |
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Sprache: | eng |
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Zusammenfassung: | 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 disease mapping 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. |
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ISSN: | 1089-7771 2168-2194 1558-0032 2168-2208 |
DOI: | 10.1109/TITB.2009.2024144 |