Center to Enable Research, Training Opportunities in Computational Biology
Most people picture a biologist cataloging wildlife or observing cells under a microscope. They might not imagine someone analyzing a computerized model of how an aspect of life works. Mike Colvin at UC Merced says that's all about to change.
The U.S. Department of Energy's Office of Advanced Scientific Computing has awarded a three-year, $900,000-per-year grant to UC Merced to help establish a Center for Computational Biology (CCB), with Colvin as director and Arnold Kim as deputy director. UC Merced is collaborating with other institutions such as Rensselaer Polytechnic Institute and Lawrence Livermore National Laboratory to develop the CCB.
We plan to increase the role of math and computer science in biology, and to attract and retain a new generation of biologists whose research depends on that interaction, says Colvin. Researchers at the CCB will use computer simulations to help understand situations traditionally studied by biologists, such as how cancer cells interact with drugs used to treat the disease.
The UC Merced CCB is one of three such centers being created by the Department of Energy. The other two are located at the University of Wisconsin and the Johns Hopkins University.
The UC Merced group is planning computer-oriented materials for life sciences courses that will make the newest research methods and results available to students, to be dispersed for free through the Connexions courseware system at Rice University. Graduate students at UC Merced will use elements of these materials in Fall 2004. Undergraduate students will use and assess the new courses in Fall 2005.
This training comes just in time, says Colvin.Biology is no longer a science of cataloging and memorization; there's important discovery going on at the most basic levels of life, he explains.Today's fastest computers are nearly a million times faster than the supercomputers of 20 years ago. The difference in what we can accomplish is amazing.
The CCB will develop methods to translate that computer power into improved biological understanding. This should create increased job marketability and security for students who benefit from its programs, as well as progress for the larger scientific community.