30 citations · 33 across the 3 of their papers we have counts for
4 papers
Handling highly correlated genes in prediction analysis of genomic studies
Li Xing, Songwan Joun, Kurt Mackay +2
Background: Selecting feature genes to predict phenotypes is one of the typical tasks in analyzing genomics data. Though many general-purpose algorithms were developed for predicti…
Simultaneous prediction of multiple outcomes using revised stacking algorithms
Li Xing, Mary Lesperance, Xuekui Zhang
Motivation: HIV is difficult to treat because its virus mutates at a high rate and mutated viruses easily develop resistance to existing drugs. If the relationships between mutatio…
A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genetics
Keelin Greenlaw, Elena Szefer, Jinko Graham +2
Motivation: Recent advances in technology for brain imaging and high-throughput genotyping have motivated studies examining the influence of genetic variation on brain structure. W…
Regularization Parameter Selection for a Bayesian Multi-Level Group Lasso Regression Model with Application to Imaging Genomics
Farouk S. Nathoo, Keelin Greenlaw, Mary Lesperance
We investigate the choice of tuning parameters for a Bayesian multi-level group lasso model developed for the joint analysis of neuroimaging and genetic data. The regression model…