Blacksburg, VA, USA. Math-based computer models are a powerful tool for discovering the details of complex living systems. John Tyson, professor of biology at Virginia Tech, is creating such models to discover how cells process information and make decisions.

"Cells receive information in the form of chemical signals, physical attachments to other cells, or radiation damage, for instance," Tyson said. The cells then must make use of this complex information to make the correct response, such as to grow and divide, or even to stop growing and repair any damage, or to just give it up and commit suicide.

The question for a molecular biologist is: What are the underlying molecular mechanisms that implement these information processing systems? "Just as computer is an information processing system, with silicon chips, wires, mother board, clock, and power source, a cell is a an information processing system made of genes, messenger RNAs, proteins, and enzymes," Tyson said. "Somehow these molecules interact with each other to detect signals, make decisions, and implement the proper response."

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Tyson presented his findings at the American Association for the Advancement of Science 2010 Annual Meeting on 18-22 February 2010, as part of a session on Moving Across Scales: Mathematics for Investigating Biological Hierarchies.

Tyson talked about Molecular Network Dynamics and Cell Physiology, or the cell as an information-processing system.

All of the speakers illustrated how math models help scientists reason across scales in biology.

The range of interest extended from interactions between sick and healthy people to the spread of global pandemics. Whereas models of this sort can inform public health decisions on a global scale, Tyson's research addresses basic science at the smallest scale — bridging the gap from molecules to cells.

"We have to first understand the molecular basis of normal cell behavior; then we have a chance of figuring out how the system is broken in diseased cells," said Tyson. "What decision-making processes tell a cell when to grow and divide and when to just hang-out?"

Mistakes in this decision process that cause both condition and disease states like cancer. Both are caused, at least in part, by faulty decision-making at the cellular level. The cells are no longer obeying the rules. Tyson says "We know the cause is in the molecules that are supposed to be enforcing these rules".

During the course of his research, Tyson and colleagues have used computer simulations to test their math models. "If the math model behaves in the computer the way cells behave in the lab, we gain confidence that we understand the molecular interactions correctly. If not, we can be sure that our models are missing something important."

Tyson talked about the control of cell division in yeast and in mammalian cells. "Yeast cells are easy to work with in the lab, and their molecular control systems are very similar to the control systems in mammalian cells," he said As a result of the success that Tyson and his colleagues have had in modeling yeast cell growth and division, they are now making the transition to mammalian cells and cancer.

"We do not yet have an engineer's understanding of normal mammalian cell proliferation and of what goes wrong in cancer cells," Tyson said. "Cancer treatment is still a matter of cutting out, blasting, or poisoning cancer cells — and any normal cells that get in the way.

We could be more subtle and perhaps more effective in treating cancers if we had a systematic insider's understanding of the molecular networks that control cell growth, division and death, and an ability to manipulate this control system with a new array of drugs and procedures."

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