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Computational Protein Structure Prediction

The purpose of this workshop is to help identify and roadmap those issues in the use of high performance computing in structural prediction that are critical to the success of the Genomes to Life (GTL) program (http://doegenomestolife.org).

Workshop Date:

Computational Protein Structure Prediction, July 24, 2003

Participation in each workshop is by invitation only.

When making your hotel reservation, please refer to the GTL workshop block.

The workshop is sponsored by the Department of Energy Offices of Advanced Scientific Computing Research and Biological and Environmental Research.

Computational Protein Structure Prediction
July 24, 2003

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. (www.doegenomestolife.org)

With this promise, however, comes a problem with the massive quantities and increased complexity of biological data produced by experiments and computations. Genome-scale collection, analysis, dissemination, and modeling of those data are the key to success of GTL. Most of these activities that deal with data generated by specialized experimental facilities will be performed primarily at these facilities. However, integration and coordination of collection, analysis, and dissemination of data across the facilities will be extremely critical to assure high-throughput knowledge synthesis, engage the broader biology community, and to eventually bring genomes to life. The pressing need for such integration was emphasized by the GTL facility plan and numerous workshop reports.

The Genomes-to-Life Structure Prediction Workshop will seek to address these integration requirements as well as scope out the major capabilities and problems associated with the full scale distributed GTL facility.

The GTL Structure Prediction Workshop will address both hardware and software infrastructure and span the following four areas:

  • Creation of a GTL data management infrastructure that will make the growing body of, distributed, biological data available in a form suitable for study and use by the general biology community.

  • Development and deployment of a data analysis and knowledge-enabling infrastructure that supports a rapid application development environment for creating and managing sophisticated, distributed data mining processes.

  • Development of the next generation data algorithms and tools that will allow biologists to derive inferences from massive amounts of complex, heterogeneous, and distributed biological data.

  • Provisioning the state-of-the-art computational facilities targeting GTL data analysis, modeling and visualization needs for existing GTL projects as well as future GTL facilities.

The 20 invited participants will be asked to address the cross-cutting GTL tool and data needs of the four proposed GTL facilities, the five large GTL projects currently funded, and the larger DOE biology community. The results of this workshop will be published in a report to DOE.


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