First it was chess. Then it was Jeopardy.

Now computers are at it again, but this time they are trying to automate the scientific process itself.

Using a Cornell-developed software called Eureqa, an interdisciplinary team of scientists that includes Cornell's Hod Lipson has demonstrated that a computer can analyze raw experimental data from a biological system and derive the mathematical equations that describe how the system operates. It is one of the most complex scientific modeling problems that a computer has solved completely from scratch, say the researchers.

"Biology is the area where the gap between theory and data is growing most rapidly," said Lipson, associate professor of mechanical and aerospace engineering and of computing and information science. "So it is the area in greatest need of automation."

The research is published in the October issue of Physical Biology.

The team -- which is led by researchers from Vanderbilt University and includes Lipson; Cornell graduate student Michael Schmidt; and researchers from CFD Research Corp. -- used Eureqa to study glycolysis, the primary process that produces energy in a living cell. Specifically, they focused on the manner in which yeast cells control fluctuations in the chemical compounds produced by the process.

The researchers used one of the process' detailed mathematical models to generate a data set corresponding to the measurements a scientist would make under various conditions. When they fed the data into Eureqa, it derived a series of equations that were nearly identical to the known equations.

Lipson and Schmidt originally created Eureqa to design robots without going through the normal trial-and-error stage that is both slow and expensive. They realized later that it could be applied to solving science problems.

The research was funded by the National Science Foundation, National Institutes of Health, the Defense Threat Reduction Agency and the National Academies Keck Futures Initiative.