AIMC Topic: Genome-Wide Association Study

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Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

PloS one Feb 27, 2020
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two w...
Cancer Survivors Germ Cells Neoplasms, Radiation-Induced Cohort Studies Polymorphism, Single Nucleotide Genotype Breast Neoplasms Case-Control Studies Genome-Wide Association Study Humans Machine Learning Young Adult Adult Female Risk Factors
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GenEpi: gene-based epistasis discovery using machine learning.

BMC bioinformatics Feb 24, 2020
BACKGROUND: Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with ...
Genome-Wide Association Study Epistasis, Genetic Machine Learning Software Phenotype Humans
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A genome-wide multiphenotypic association analysis identified candidate genes and gene ontology shared by four common risky behaviors.

Aging Feb 22, 2020
BACKGROUND: Risky behaviors can lead to huge economic and health losses. However, limited efforts are paid to explore the genetic mechanisms of risky behaviors.
Phenotype Autism Spectrum Disorder Transcriptome Humans Intelligence Gene Ontology Genome-Wide Association Study Neurogenesis Genetic Predisposition to Disease Risk-Taking Polymorphism, Single Nucleotide
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DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

PLoS computational biology Feb 3, 2020
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses...
Multivariate Analysis Quantitative Trait Loci Humans Polymorphism, Single Nucleotide Deep Learning Genetic Association Studies Genome-Wide Association Study
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Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

eLife Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Signal Transduction Models, Theoretical Chromatin Genetic Predisposition to Disease Polymorphism, Single Nucleotide Epigenomics Islets of Langerhans Genome-Wide Association Study Diabetes Mellitus, Type 2 Humans Deep Learning
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Next-generation drug repurposing using human genetics and network biology.

Current opinion in pharmacology Jan 22, 2020
Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatmen...
Animals Genome-Wide Association Study Gene Regulatory Networks Drug Repositioning Humans Machine Learning Genetic Therapy Human Genetics
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Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

Chest Dec 28, 2019
COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year lo...
Molecular Epidemiology Cluster Analysis Diagnostic Imaging Respiratory Function Tests Pulmonary Disease, Chronic Obstructive Disease Progression Genome-Wide Association Study Genetic Predisposition to Disease Humans Machine Learning Phenotype
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Machine Learning Enables High-Throughput Phenotyping for Analyses of the Genetic Architecture of Bulliform Cell Patterning in Maize.

G3 (Bethesda, Md.) Dec 3, 2019
Bulliform cells comprise specialized cell types that develop on the adaxial (upper) surface of grass leaves, and are patterned to form linear rows along the proximodistal axis of the adult leaf blade. Bulliform cell patterning affects leaf angle and ...
Quantitative Trait, Heritable Plant Leaves Machine Learning Zea mays Genome-Wide Association Study Gene Expression Regulation, Plant
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TSLRF: Two-Stage Algorithm Based on Least Angle Regression and Random Forest in genome-wide association studies.

Scientific reports Dec 2, 2019
One of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods a...
Genomics Polymorphism, Single Nucleotide Models, Genetic Genome, Plant Quantitative Trait Loci Multigene Family Linear Models Machine Learning Genome-Wide Association Study Arabidopsis
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Brain age prediction using deep learning uncovers associated sequence variants.

Nature communications Nov 27, 2019
Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual's predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here...
United Kingdom Neuropsychological Tests Iceland Genome-Wide Association Study Young Adult Middle Aged Brain Humans Polymorphism, Single Nucleotide Adult Deep Learning Aged Neural Networks, Computer Aging Magnetic Resonance Imaging Adolescent Aged, 80 and over Databases, Factual
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