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
Link To Document :
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