High-throughput genetic screens have exponentially increased the functional annotation of the genome over the past 10 years. Likewise, genome-scale efforts to map DNA methylation, chromatin state and occupancy, messenger RNA expression patterns, and disease-associated genetic polymorphisms, and proteome-wide efforts to map protein-protein interactions, have also created vast resources of data. An emerging trend involves combining multiple types of data, referred to as integrative screening. Examples include papers that report integrated data generated from large-scale RNA interference screens on the Wnt/beta-catenin pathway with either genotypic or proteomic data in colorectal cancer. These studies demonstrate the power of data integration to generate focused, validated data sets and to identify high-confidence candidate genes for follow-up experiments. We present the ongoing evolution and new strategies for the integrative screening approach with respect to understanding and treating human disease.