Radcliffe conference looks at biological systems

With the rapid advance of technology opening new frontiers of knowledge, the Radcliffe Institute for Advanced Study looked at the increasingly detailed understanding of biological systems last week (May 6) as well as the potential of that knowledge for future applications.
The Radcliffe Institute’s “Designing Biology” conference drew about 300 to a daylong program of talks, panel discussions, and poster sessions about the cutting edge of biology and how our increasingly detailed understanding of biological systems can be used to influence how they operate.

Radcliffe Institute Dean of Science Barbara Grosz, Higgins Professor of Natural Sciences, opened the event, saying that the Radcliffe Institute’s science programs aim to bring people together across disciplinary lines through events such as last week’s conference.

The conference was sponsored by the institute, by Harvard’s Nanoscale Science and Engineering Center, and by Harvard’s Biomechanics Ph.D. program.

Ellen Williams, Distinguished University Professor at the Institute for Physical Science and Technology at the University of Maryland, provided historical perspective for the day. She said that whether people realize it or not, we’re living in a time of revolutionary change in the biological sciences.

Williams traced the beginning of the revolution to 20 years ago, when the scanning probe microscope was invented. The microscope allowed scientists for the first time to understand the behavior of individual molecules, a large step forward from earlier work, which was based on observations of the average properties of large groups of molecules.

While the scanning probe microscope got things started, Williams said today there’s a “whole raft of new tools and capabilities” that are helping researchers probe ever deeper into the basic processes of life.

“It’s difficult to recognize when you’re living in the middle of a revolution, but I think we are,” Williams said.

The complexity of biological molecules and systems has proven hard to unravel, Williams said, but this complexity is yielding its secrets to today’s researchers, who have begun to use their learning to manipulate these systems.