Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2019
Noncoding single nucleotide polymorphisms (SNPs) and their target genes are important components of the heritability of diseases and other polygenic traits. Identifying these SNPs and target genes could potentially reveal new molecular mechanisms and...
Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to...
BACKGROUND: The inflammatory bowel diseases (IBDs) are chronic inflammatory disorders, associated with genetic, immunologic, and environmental factors. Although hundreds of genes are implicated in IBD etiology, it is likely that additional genes play...
MOTIVATION: Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to det...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2017
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...
MOTIVATION: Gene-gene interaction (GGI) is one of the most popular approaches for finding and explaining the missing heritability of common complex traits in genome-wide association studies. The multifactor dimensionality reduction (MDR) method has b...
International journal of data mining and bioinformatics
Jan 1, 2015
Genome-wide Association Studies (GWAS) have resulted in many discovered risk variants for several obesity-related traits. However, before clinical relevance of these discoveries can be achieved, molecular or physiological mechanisms of these risk var...
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