Rutgers to start up National Program of Excellence in Biomedical Computing
NEW BRUNSWICK/PISCATAWAY, N.J. -- Rutgers has been selected by the National Institutes of Health (NIH) to develop a National Program of Excellence in Biomedical Computing. The Bethesda, Md.-based NIH is providing a $1.35 million grant to Rutgers over a three-year period to fund "phase one" planning and startup. The university is one of only four institutions out of a field of 26 applicants to receive funding under this program. This grant is awarded as part of the NIH's "Biomedical Information Science and Technology Initiative."
"This program is a new strategy for NIH," said Ronald M. Levy, principal investigator on the NIH grant and professor of chemistry and chemical biology at Rutgers. "It acknowledges that biomedical research has become increasingly dependent on computing to manage and analyze data, and to model biological processes. We saw this in the Human Genome Project with its massive amounts of data and analysis. While the NIH program isn't limited to or directly related to the genome project, it is inspired by the notion that computing now plays a major central role in biology."
The phase one funding will enable Rutgers to assemble what NIH calls a Leadership Group, develop an initial research project in biomedical computing that spans a number of different disciplines, set up a graduate training program and provide the necessary laboratory infrastructure for the students.
"An integral part of the NIH Rutgers program is the training of students," said Joseph J. Seneca, university vice president for academic affairs. "The plan is closely affiliated with a new and exciting Rutgers initiative for research and education at the interface of the biological, mathematical and physical sciences. Know by the acronym BioMaPS, this initiative provides for the establishment of a graduate program, graduate courses, undergraduate courses, summer research internships and seminars at this interdisciplinary interface."
BioMaPS began as a Rutgers Strategic Resource and Opportunity Analysis (SROA) project, part of a reallocation plan that shifts administrative savings to academic priorities. As an annual revolving resource of $4 million, the SROA program is an important source of university funding for its strategic priorities.
The co-principal investigator for Rutgers' National Program of Excellence in Biomedical Computing is Richard H. Ebright, professor of chemistry and chemical biology and Howard Hughes Medical Institute investigator at Rutgers' Waksman Institute of Microbiology. Levy and Ebright will work with a multidiscipinary leadership team, initially comprising seven other Rutgers investigators together with collaborators from other institutions. These include: Helen M. Berman, Wilma K. Olson and Emilio Gallicchio (department of chemistry and chemical biology), Tomasz Imielinski (department of computer science), Andrei E. Ruckenstein (department of physics), Konstantin Severinov (department of genetics), Eduardo D. Sontag (department of mathematics), Michael Elowitz and Milton Werner (Rockefeller University, New York), and Boris Shraiman (Bell Laboratories, Murray Hill). The group plans to recruit additional members to the team.
The team will focus its efforts on studying the biology of transcription and the regulation of gene expression.
Transcription is the process through which the communication of genetic information begins. The information coded on the DNA is mapped onto proteins that carry it to other molecules and cells where it may be "expressed." Gene expression underlies important biological processes including development, immune defenses, and tumor formation. Many cancers are known to result from mutations that alter the way genes are expressed. Deciphering the molecular mechanisms that govern gene expression is crucial in the search for solutions to pressing human health problems such as cancer and infectious diseases.
"We are going to be studying the structural biology of transcription and regulation, the statistical physics associated with it, computer modeling of the elementary molecules that come together to regulate expression, and modeling or simulating the time evolution of transcription and the interaction of genes through kinetic models at a higher level of modeling," said Levy.