Hope College has received a $1.2 million grant from the National Science Foundation (NSF) for a project that is linking three Hope departments and three institutions in developing computer models for genetic research.

The support will enable faculty and students in the departments of biology, computer science and mathematics to expand an ongoing research effort at Hope to develop software to model microbial metabolism based on information encoded in microbial genomes.  The resulting package will ultimately become part of the RAST (Rapid Annotation using Subsystems Technology) genome analysis service available to researchers internationally through Argonne National Laboratory in Illinois.

The goal of the Hope project is to provide integrated, automated tools that can assist researchers internationally to analyze the genomes, model the way the metabolism works and provide tools for analyzing regulatory data.

"The pace of genetic sequencing is increasingly exponentially, and there's more data than can be analyzed manually," said Dr. Matt DeJongh, who is an associate professor of computer science and leading the project with Dr. Aaron Best of the biology faculty and Dr. Nathan Tintle of the mathematics faculty.  "By putting all three pieces together, we're hoping to be able to make predictions about metabolism and regulation in bacteria, and to do so more efficiently than would be possible using disparate tools in different locations with different interfaces."

The work is in the field of bioinformatics, which blends biology and computer science in managing and analyzing genetic data compiled through projects such as the Human Genome Project.

The RAST server is a major component of the SEED project, a nationwide, open-source effort to develop and share genomic data.  Its services are available at no charge and are used by more than 200 external institutions to annotate 150 to 200 genomes per month.  It is accessible through a Web interface, with researchers uploading genome sequences and receiving functional annotations and other data in response.

The Hope researchers have most recently been working through a three-year, $235,022 NSF grant that they received last fall.  The new $1,267,183 grant will provide support for two years beginning in September, and will further expand the project by enabling Hope to partner with the Fellowship for Interpretation of Genomes (FIG) of Burr Ridge, Ill., and the Burnham Institute for Medical Research of La Jolla, Calif.

Best, DeJongh and Tintle are also all supported in their research individually with four-year Towsley awards from Hope, funded through an endowment made possible through a grant from the Harry A. and Margaret D. Towsley Foundation, presented to them in 2007, 2005 and 2008 respectively.  In addition, they have also been supported through a grant that Hope received in 2004 from the Howard Hughes Medical Institute for several initiatives in the sciences, including collaborative research with students in computational modeling.

Hope's emphasis through the new NSF grant, as through the previous one, will be on developing the modeling software, with additional focus on some of the analysis tools.  The Burnham Institute will also be working on analysis tools, and FIG will work at integrating the software into the RAST system.

Students in all three of the Hope departments will be working on the project in collaboration with Best, DeJongh and Tintle.  A total of seven students will conduct research full-time each summer through the two NSF grants, with two working part-time during the school year.