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Advancements in high-throughput omics technologies have provided an unprecedented opportunity for cancer studies. At the same time, advanced technologies have led to an increasing gap between data generation and investigators’ ability to interpret the vast amount of interconnected data. In this talk, I will briefly review different bioinformatics approaches for omics data integration and demonstrate their applications using genomic and proteomic data generated from the TCGA (The Cancer Genome Atlas) and CPTAC (Clinical Proteome Tumor Analysis Consortium) projects. I will also introduce NetGestalt, a novel data integration framework that allows simultaneous presentation of large-scale experimental and annotation data from various sources in the context of a biological network to facilitate data visualization, analysis, interpretation, and hypothesis generation.