Recent advances of -omics technologies have stimulated a large body of biomedical studies focused on the discovery and characterization of molecular mechanisms of various diseases. For example, many studies have been focused on the identification of genes to diagnose or predict cancer. The rapid expansion of complex and large -omics datasets has nourished the development of tailored statistical methods to address the challenges that have arisen in the field. Some examples are detection and correction of biases and artifacts in raw high throughput -omics data, identification of true signal among a large number of variables measured on a much smaller number of subjects, modeling of complex covariance structures, integration of diverse -omics datasets. Research in this area is characterized by multidisciplinary collaborations among researchers from Statistics, Computer Science, Medical Genetics, Molecular Biology, and other related fields.