Integrative omics and high dimensional network inference Tumors are complex disease. No single type of molecular approach fully elucidates tumor behavior, necessitating analysis at multiple levels encompassing genomics and proteomics. Therefore different types of data from numerous sources are now collected at a genome-wide scale, including: DNA copy number alterations, mRNA expression, protein expression measurements and many others. We are interested in developing computational/statistical methods for integrating different types of genomics/proteomics (omics) data so that better prevention and therapeutic intervention strategies can be developed for patients. And network is a powerful tool for this purpose.