AIMC Topic: Genome-Wide Association Study
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Machine Learning-Based Gene Prioritization Identifies Novel Candidate Risk Genes for Inflammatory Bowel Disease.
Inflammatory bowel diseases
Sep 1, 2017
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...
CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.
Bioinformatics (Oxford, England)
Aug 1, 2017
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...
Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.
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...
A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions.
Bioinformatics (Oxford, England)
Sep 1, 2016
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...
Genetic variation and alternative splicing.
Nature biotechnology
Apr 1, 2015
RNA. Prescribing splicing.
Science (New York, N.Y.)
Jan 9, 2015
Prescribing splicing
Discovery of phenotypic networks from genotypic association studies with application to obesity.
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...
Epistasis analysis using multifactor dimensionality reduction.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
Here we introduce the multifactor dimensionality reduction (MDR) methodology and software package for detecting and characterizing epistasis in genetic association studies. We provide a general overview of the method and then highlight some of the ke...
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