Beyond the main genetic and environmental effects, gene–environment (G–E) interactions
have been demonstrated to significantly contribute to the development and progression of …

Variable selection methods have been extensively developed for and applied to cancer
genomics data to identify important omics features associated with complex disease traits …

This paper proposes a parametric hierarchical model for functional data with an elliptical
shape, using a Gaussian process prior to capturing the data dependencies that reflect …

Data irregularity in cancer genomics studies has been widely observed in the form of outliers
and heavy-tailed distributions in the complex traits. In the past decade, robust variable …

Variable selection is a commonly used method for analyzing genomic data with high
dimensionality. It has been designed to handle complicated data structures and facilitate the …

In longitudinal studies, the same subjects are measured repeatedly over time, leading to
correlations among the repeated measurements. Properly accounting for the intra-cluster …