Genomes to Life Program Contacts for program information

three one-day workshops were held in Gaithersburg, Maryland. Each was attended by about 30 computational biologists, mathematicians, and computer scientists who were experts in the respective workshop areas. The first workshop discussed data infrastructure needs for the Genomes to Life (GTL) program with the objective of identifying current gaps and defining the infrastructure required for the success of the proposed GTL facilities. The second workshop discussed modeling and simulation needs for the next phase of the GTL program and defined how these relate to experimental data generated by genomics, proteomics, and metabolomics. The third workshop identified emerging technical challenges in computational protein structure prediction for DOE missions and outlined specific goals for the next phase of GTL. The workshops were attended by representatives from both the Office of Biological and Environmental Research and the Office of Advanced Scientific Computing Research. Invited experts at each workshop made short presentations on what they perceived as key needs in GTL data infrastructure, modeling and simulation, and structure prediction, respectively. Each presentation was followed by a lively discussion by all attendees. The following findings and recommendations were derived from the three workshops. A seamless integration of GTL data spanning the entire range of genomics, proteomics, and metabolomics will be extremely challenging but must be treated as the primary component of the GTL program to ensure GTL's chances for success. High-throughput GTL facilities and ultrascale computing will make it possible to address the ultimate goal of modern biology: To achieve a fundamental, comprehensive, and systematic understanding of life. But first the GTL community needs to address the massive quantities and increased complexity of biological data produced by experiments and computations. Genome-scale collection, analysis , dissemination, and modeling of data are key to GTL's success. Localizing these activities within each experimental facility that generates data will ease integration and organization. However, integration and coordination of these activities across the facilities will be extremely critical to ensure high-throughput knowledge synthesis and engage the broader biology community. Ultimately, the success of the data infrastructure will be judged by how well it is accepted by and serves the biology community. Executive Summary 2 Recommendations • DOE should lay the groundwork for a GTL data infrastructure composed of a distributed but integrated suite of facilities databases, through the cooperative development of data models and database schemas. This process should seek to identify shared or common data elements, objects, concepts, and …