TAG SNP SELECTION USING CLONAL SELECTION ALGORITHM BASED ON SUPPORT VECTOR MACHINE
Küçük Resim Yok
Tarih
2011
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
AMER SOC MECHANICAL ENGINEERS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Investigations on genetic variants associated with complex diseases are important for enhancements in diagnosis and treatments. SNPs (Single Nucleotide Polymorphisms), which comprise most of the millions of changes in human genome, are promising tools for disease-gene association studies. On the other hand, these studies are limited by cost of genotyping tremendous number of SNPs. Therefore, it is essential to identify a subset of SNPs that represents rest of the SNPs. As subset of SNPs is identified, data set should be searched as well as possible. In this study, a new method called CLONTagger was introduced, where Support Vector Machine (SVM) was used as SNP prediction method, whereas Clonal Selection Algorithm (CLONALG) was used as tag SNP selection method. The suggested method was compared with current tag SNP selection algorithms in literature using different datasets. Experimental results demonstrated that the suggested method could identify tag SNPs with better prediction accuracy than other methods from literature.
Açıklama
3rd International Conference on Future Computer and Communication (ICFCC 2011) -- JUN 03-05, 2011 -- G Enescu Univ Arts, Iasi, ROMANIA
Anahtar Kelimeler
Single Nucleotide Polymorphisms (SNPs), Tag SNPs, Clonal Selection Algorithm (CLONALG), Support Vector Machine (SVM)
Kaynak
PROCEEDINGS OF THE 2011 3RD INTERNATIONAL CONFERENCE ON FUTURE COMPUTER AND COMMUNICATION (ICFCC 2011)
WoS Q Değeri
N/A
