  After the completion of human genome sequence was anounced, it is evident
that interpretation of DNA sequences is an immediate task to work on. For
understanding their signals, improvement of present sequence analysis tools and
developing new ones become necessary. Along this current trend, we attack one
of the fundamental questions, which set of SNP(single nucleotide polymorphism)
variations is related to a specific disease or trait is. For, in the whole DNA
sequence, it is known that people have different DNAs only at SNP locations,
and moreover, the total SNPs are less than 5 millions, finding an association
between SNP variations and certain disease or trait is believed to be one of
the essential steps not only for genetic researches but for drug design and
discovery. In this paper, we are going to present a method of detecting whether
there is an association between multiple SNP variations and a trait or disease.
The method exploits the Support Vector Machine which has been attracting lots
of attentions recently.
