Across many cancers and within the majority of individual tumors, a large number of genes are disrupted. Prioritizing these genes on the basis of their function and classifying them into cellular pathways and processes is essential to interpreting cancer genomics and guiding future therapeutic approaches. To complement the traditional and powerful approach of deeply studying these genes one-by-one, we are using systematic approaches to study all candidate genes in massively parallel fashion. For example, we have developed approaches to deploy gene signature profiling in high-throughput (Connectivity Map/L1000 Project) which is being used to examine the molecular consequences of each cancer mutation and identify pathway relationships between altered genes. For more information, please see our LINCS page and an overview of the Target Accelerator.