DocumentCode
1987954
Title
Haplotype pattern mining & classification for detecting disease associated site
Author
Kido, Takashi ; Baba, Masanori ; Matsumine, Hirohito ; Higashi, Yoko ; Higuchi, Hirotaka ; Muramatsu, Masaaki
Author_Institution
HuBit Genomix Inc., Tokyo, Japan
fYear
2003
fDate
11-14 Aug. 2003
Firstpage
452
Lastpage
453
Abstract
Finding the causative genes for common diseases using SNP (single nucleotide polymorphism) markers is now becoming a real challenge. Although traditional statistical SNP association tests exist, these tests could not explain the effects of SNP combinations or probable recombination histories from ancestral chromosomes. Haplotype analysis of disease associated site provides more powerful markers than individual SNP analysis, and can help identify probable causative mutations. In this paper, we introduce a new method for effective haplotype pattern mining to detect disease associated mutations. Using this procedure, we can discover some of the new disease associated SNPs, which can not be detected by traditional methods. We will introduce a powerful tool for implementing this procedure with some worked examples.
Keywords
biology computing; data mining; diseases; genetics; organic compounds; pattern classification; polymorphism; SNP combinations; ancestral chromosomes; causative genes; causative mutations; disease associated site detection; haplotype pattern mining; pattern classification; recombination history; single nucleotide polymorphism markers; statistical SNP association test; Bioinformatics; Dentistry; Diseases; Frequency estimation; Genetic mutations; Genomics; Phylogeny; Poles and towers; Testing; Tree graphs;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE
Print_ISBN
0-7695-2000-6
Type
conf
DOI
10.1109/CSB.2003.1227369
Filename
1227369
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