CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs

Authors:
S. I. Ao;Kevin Yip;Michael Ng;David Cheung;Pui-Yee Fong;Ian Melhado;Pak C. Sham
Affiliations:
Department of Mathematics, The University of Hong Kong Pokfulam, Hong Kong;Department of Computer Science, The University of Hong Kong Pokfulam, Hong Kong;Department of Mathematics, The University of Hong Kong Pokfulam, Hong Kong;Department of Computer Science, The University of Hong Kong Pokfulam, Hong Kong;Genome Research Center, The University of Hong Kong Pokfulam, Hong Kong;Genome Research Center, The University of Hong Kong Pokfulam, Hong Kong;Genome Research Center, The University of Hong Kong Pokfulam, Hong Kong
Venue:
Bioinformatics
Year:
2005

Citing 0
Cited 10

A new framework for the selection of tag SNPs by multimarker haplotypes

Journal of Biomedical Informatics
Computational intelligence for genetic association study in complex diseases: review of theory and applications

International Journal of Computational Intelligence in Bioinformatics and Systems Biology
Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases

IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Investigation of a new GRASP-based clustering algorithm applied to biological data

Computers and Operations Research
SKM-SNP: SNP markers detection method

Journal of Biomedical Informatics
A Fast Quartet tree heuristic for hierarchical clustering

Pattern Recognition
Multiple ant colony algorithm method for selecting tag SNPs

Journal of Biomedical Informatics
A genetic algorithm-support vector machine method with parameter optimization for selecting the tag SNPs

Journal of Biomedical Informatics
Maximum domination problem

CATS '11 Proceedings of the Seventeenth Computing: The Australasian Theory Symposium - Volume 119
Maximum domination problem

CATS 2011 Proceedings of the Seventeenth Computing on The Australasian Theory Symposium - Volume 119

Quantified Score

Hi-index	3.84

Visualization

Abstract

Summary: Cluster and set-cover algorithms are developed to obtain a set of tag single nucleotide polymorphisms (SNPs) that can represent all the known SNPs in a chromosomal region, subject to the constraint that all SNPs must have a squared correlation R2 C with at least one tag SNP, where C is specified by the user. Availability: http://hkumath.hku.hk/web/link/CLUSTAG/CLUSTAG.html Contact: mng@maths.hku.hk