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NSF Bioinformatics Awards, Jan. 1 -- Feb. 4, 2006

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High-Performance Algorithms for Scientific Applications. Start date: Dec. 1, 2005. Expires: Dec. 31, 2006. Expected total amount: $108,037. Principal investigator: David Bader. Sponsor: Georgia Tech Research Corp.

Supports a project to develop, implement, assess, and refine algorithms for symmetric multiprocessor clusters to speed irregular computations, such as string-, tree-, and graph-based computations. The research will focus on "science-driven" problems in genomics, bioinformatics, and computational ecology.


Developing Web Services for the Arabidopsis Community. Start date: Feb. 1, 2006. Expires: Jan. 31, 2007. Expected total amount: $187,621. Principal investigator: Christopher Town. Sponsor: Institute for Genomic Research.

Funds development of a prototype procedure and tools to implement web services on a small number of databases in the Arabidopsis community. The demonstration project will deploy web services at approximately eight research sites in the US that vary both in the kinds of data that they host, and in the level of expertise of the investigators at the sites. The results of these efforts will be reported and demonstrated at the annual International Arabidopsis Research Conference.


Novel Statistical Models and Computational Algorithms for Evolutionary Genomics. Start date: March 1, 2006. Expires: Feb. 28, 2007. Expected total amount: $1,312,321. Principal investigator: Eric Xing. Sponsor: Carnegie Mellon University.

Funds development of computational methods and theoretical models to study the evolutionary mechanisms and processes that shape transcription regulatory network in metazoan species. Project goals include developing new methods for deciphering the cis-regulatory codes and the transcriptional regulatory networks in metazoan species; developing new theories and algorithms for modeling regulatory evolution based on structural and functional transformations of regulatory elements; and developing algorithms for comparative genomic and network inference based on the new formalism of structural/functional phylogeny.


An Integrated Approach to the Study of Biological Process Specific Networks. Start date: June 1, 2006. Expires: May 31, 2007. Expected total amount: $1,000,692. Principal investigator: Olga Troyanskaya. Sponsor: Princeton University.

Supports development of an integrated computational and experimental approach for modeling biological pathways and networks. This technology will consist of three integrated components: a computational component for generalizable, efficient, and accurate integration of diverse genomic data; an analytical component for network/pathway modeling based on the integrated data; and an experimental component for validation and feedback.


Acquisition of Computational Chemistry Resources for Research and Education. Start date: Feb. 15, 2006. Expires: Jan. 31, 2009. Expected total amount: $353,660. Principal investigator: Gregory Girolami. Sponsor: University of Illinois, Urbana-Champaign.

Funds the purchase of three computers for computational chemistry research and education to support projects including electronic structure calculations, theoretical reaction dynamics and photochemistry, intramolecular energy transfer and coherent control, semiclassical and quantum dynamics of condensed phase processes, statistical mechanics of polymers and complex fluids, molecular dynamics simulation of biological processes, protein folding, and bioinformatics.


Comparative Genomics of Gene Family Evolution. Start date: Feb. 1, 2006. Expires: Jan. 31, 2007. Expected total amount: $50,000. Principal investigator: Matthew Hahn. Sponsor: Indiana University.

Supports the application of a previously developed stochastic birth and death model for gene family evolution to multi-species genome comparisons. The investigator will use the model to identify large-scale patterns in genome evolution and make stronger inferences regarding the role of natural selection in gene family expansion or contraction. The goals of this project are to extend the statistical methodology available for making inferences using the birth and death model. The project will result in the production of a freestanding software package that the investigator will make available to the research community.

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The Scan

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