A Geometrical Model for the SNP Motif Identification Problem
Gaofeng Huang and Peter Jeavons abstract
A common type of DNA variation is called a Single Nucleotide Polymorphism (SNP), where a single position within a DNA sequence is altered from one nucleotide base to another. The problem of identifying disease-associated SNPs has been the subject of extensive research by statisticians. However, less research has been done within the computing community. In this paper, we propose a novel geometrical computing model for the SNP Motif Identification Problem. The purpose of our research is to explore the properties of SNPs in a combinatorial way. We test our algorithm on two real clinical datasets, and give computational results which demonstrate the efficiency and effectiveness of our approach.
infobook title | Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2007 |
isbn | 978-1-4244-1509-0 |
pages | 395-402 |
year | 2007 |
links
BibTeX
Link
DOI (10.1109/BIBE.2007.4375593)
related pages
|
