SKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for the association between a disease and multiple marker genotypes. We employ a subspace categorical clustering algorithm to compute a weight for each SNP in the group of patient samples and the group of normal samples, and use the weights to identify the subsets of relevant SNPs that categorize these two groups. The experiments on both Schizophrenia and Parkinson Disease data sets containing genome-wide SNPs are reported to demonstrate the program. Results indicate that our method can find some relevant SNPs that categorize the disease samples. The online SKM-SNP program is available at http://www.math.hkbu.edu.hk/~mng/SKM-SNP/SKM-SNP.html. © 2009 Elsev...
In this era of genome-wide association studies (GWAS), the quest for understanding the genetic archi...
A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between diffe...
A major challenge for genomewide disease asso-ciation studies is the high cost of genotyping large n...
AbstractSKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for t...
Single nucleotide polymorphisms (SNPs) are very common throughout the genome and hence are potential...
Several machine learning techniques have been applied for finding multi-loci associations among Sing...
Selecting a subset of SNPs (Single Nucleotide Polymorphism pronounced snip) that is informative and ...
[[abstract]]The availability of high-throughput genomic data has led to several challenges in recent...
The uniqueness of each human genetic structure motivated the shift from the current practice of medi...
We propose an algorithm for analysing SNP-based population association studies, which is a developme...
Background: Genome-wide association studies (GWAS) identify disease-associations for single-nucleoti...
Association studies for disease susceptibility genes rely on the high density of SNPs within candida...
Abstract Background Identification of disease-related genes in association studies is challenged by ...
BACKGROUND: Genome-wide association studies (GWAS) identify disease-associations for single-nucleoti...
[[abstract]]Clustering is often considered as the first step in the analysis when dealing with an en...
In this era of genome-wide association studies (GWAS), the quest for understanding the genetic archi...
A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between diffe...
A major challenge for genomewide disease asso-ciation studies is the high cost of genotyping large n...
AbstractSKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for t...
Single nucleotide polymorphisms (SNPs) are very common throughout the genome and hence are potential...
Several machine learning techniques have been applied for finding multi-loci associations among Sing...
Selecting a subset of SNPs (Single Nucleotide Polymorphism pronounced snip) that is informative and ...
[[abstract]]The availability of high-throughput genomic data has led to several challenges in recent...
The uniqueness of each human genetic structure motivated the shift from the current practice of medi...
We propose an algorithm for analysing SNP-based population association studies, which is a developme...
Background: Genome-wide association studies (GWAS) identify disease-associations for single-nucleoti...
Association studies for disease susceptibility genes rely on the high density of SNPs within candida...
Abstract Background Identification of disease-related genes in association studies is challenged by ...
BACKGROUND: Genome-wide association studies (GWAS) identify disease-associations for single-nucleoti...
[[abstract]]Clustering is often considered as the first step in the analysis when dealing with an en...
In this era of genome-wide association studies (GWAS), the quest for understanding the genetic archi...
A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between diffe...
A major challenge for genomewide disease asso-ciation studies is the high cost of genotyping large n...