We are currently in the midst a transition to virtual servers, and an update of our security status to comply with the increasingly stringent government requirements. We have successfully maintained and expanded the bulk of our Discover web-based tools, with emphasis on CellMiner and CellMinerCDB. Our CellMiner NCI-60 Analysis Tools section remains a significant resource for pharmacogenomic integration, research, and discovery. It is currently the host for four tools, i) Cell line signature, ii) Cross-correlation, iii) Pattern comparison, and iv) Drug vs gene variant/isoforms variant, all of which are designed to reduce the time required by the scientist to integrate molecular and pharmacological data. We continue to upgrade both the software and databases in this section. We currently provide the most inclusive set of molecular and largest compound activity data among any of the large-scale cellular databases. The CellMiner data and tools are creating major opportunities for progress in rational drug discovery, application, and individualization of therapy for cancer patients. As molecular alterations of many types can contribute to the outcome of therapy, the Genomic and Pharmacolgy Facility (GPF) manages and integrates molecular and pharmacological data in such a way that enhances understanding, and facilitates the generation of testable hypotheses. The GPF thus both provides access to high throughput data, and provides software resources that facilitate the mining, understanding, and exploitation of that data. As the DTP drug database contains both unexplored compounds and drugs, it remains an unmatched resource both for recognition of potential novel drugs, and improving understanding of pre-existing ones. The NCI-60 is by far the most comprehensively profiled panel of mammalian cells anywhere. CellMiner CDB expands this approach to include addition databases allowing the user to mine and integrate at will. Currently our Discover and CellMiner sites have 9,400 individual users from 110 countries per month. It has in the past and currently continues to lead to translational discoveries.
