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.
Details
| Book 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
DOI (10.1109/BIBE.2007.4375593)
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