Regularized machine learning in the genetic prediction of complex traits
Compared to univariate analysis of genome-wide association (GWA) studies, machine
learning–based models have been shown to provide improved means of learning such …
learning–based models have been shown to provide improved means of learning such …
Systems genetics analysis of genome-wide association study reveals novel associations between key biological processes and coronary artery disease
Objective—Genome-wide association studies have identified multiple genetic variants
affecting the risk of coronary artery disease (CAD). However, individually these explain only …
affecting the risk of coronary artery disease (CAD). However, individually these explain only …
A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studies
Background A central question for disease studies and crop improvements is how genetics
variants drive phenotypes. Genome Wide Association Study (GWAS) provides a powerful …
variants drive phenotypes. Genome Wide Association Study (GWAS) provides a powerful …
Meta-analysis for penalized regression methods with multi-cohort Genome-wide Association Studies
Objective: Penalized regression has been successfully applied in genome-wide association
studies. While meta-analysis is often conducted to increase power and protect patients' …
studies. While meta-analysis is often conducted to increase power and protect patients' …
[HTML][HTML] Systems Genetics Analysis of GWAS reveals Novel Associations between Key Biological Processes and Coronary Artery Disease
Objective Genome-wide association (GWA) studies have identified multiple genetic variants
affecting the risk of coronary artery disease (CAD). However, individually these explain only …
affecting the risk of coronary artery disease (CAD). However, individually these explain only …
Biological network models for inferring mechanism of action, characterizing cellular phenotypes, and predicting drug response
PJ Griffin - 2016 - search.proquest.com
A primary challenge in the analysis of high-throughput biological data is the abundance of
correlated variables. A small change to a gene's expression or a protein's binding …
correlated variables. A small change to a gene's expression or a protein's binding …
[PDF][PDF] ScholarWorks@ Georgia State Universit y
LA Hanna - 2010 - scholarworks.gsu.edu
Nadya Suleman and Kate Gosselin in the Media: Exploring Images of Motherhood and
Reproductive Technology Page 1 Georgia State University ScholarWorks @ Georgia State …
Reproductive Technology Page 1 Georgia State University ScholarWorks @ Georgia State …