Application of Support Vector Machine to detect an association between a disease or trait and multiple SNP variations
<|reference_start|>Application of Support Vector Machine to detect an association between a disease or trait and multiple SNP variations: 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.<|reference_end|>
@article{kim2001application,
    title={Application of Support Vector Machine to detect an association between a
  disease or trait and multiple SNP variations},
    author={Gene Kim and MyungHo Kim},
    journal={arXiv preprint arXiv:cs/0104015},
    year={2001},
    archivePrefix={arXiv},
    eprint={cs/0104015},
    primaryClass={cs.CC q-bio}
}