What the Heck Is Computational Biology and Why Did It Win a Nobel Prize?

Three scientists won the Nobel Prize for chemistry yesterday for pioneering methods that would become the field of computational biology as we know it today. You're thinking, that's awesome, but what the hell is computational biology? And why is it so important they awarded these guys with over a million dollars for developing it?

In a nutshell, computational biology is the practice of using computer simulations to study complicated biological processes. We're talking about really complex biological chemistry, like the interaction of cells and their environment, the reactions of proteins inside cells, and the behavior of millions of tiny atoms.

Better understanding these processes opens up a world of potential for scientists, which could lead to major breakthroughs in designing new medicines, discovering better treatments for disease, maybe even curing cancer.

Our Nobel Prize-winning scientists, Michael Levitt, Martin Karplus, and Arieh Warshel's ingenious idea of using computers to study biochemistry was revolutionary. To build models sophisticated enough to accurately simulate those kinds of complex chemical processes requires a lot of data. Huge amounts of data. And it turns out, computers are really good at storing and analyzing troves of data.

Levitt told Reuters that he had the idea to bring chemistry to computers back in the 1970s, but no one took him seriously. Nevertheless, the trio went about developing ways to interpret and express biological systems through algorithms. Today, the methods they pioneered are used in thousands of laboratories around the world.

Since the more biological information you have on hand the more you can study and learn, the software computational biologists use is almost always open source. That way other scientists can access it, add more data, and continuously build on each other's knowledge. Thus, the data set increases, and scientists are able to build larger and larger models to study and analyze.

And the future is bright. Thanks to advances in wearable technology, sensors and tracking tools, researchers can collect more information than ever, and in real-time. Eventually, it could be possible to simulate a complete living organism down to the molecular level—essentially recreating life on a machine.

Computational biology used to be considered "the poor sister, or the ugly sister, to experimental biology," Levitt said. But now simulations are so accurate they can successfully predict the outcome of traditional experiments.

So said the Swedish Academy of Sciences when it announced the award yesterday: "Today the computer is just as important a tool for chemists as the test tube," reads an academy statement. "Classical chemistry has a hard time keeping up." By letting algorithms and software do the heavy lifting, scientists can learn much more about biology and chemistry than when they were limited to conducting experiments in the lab.

Today, the technology has been used to help sequence the human genome and create models of the human brain. It can be used to screen drugs before testing them on humans or animals, or as a first pass for pharmaceutical companies experimenting with potential medicines, so they only take the most promising substances to the lab. The future breakthroughs in disease treatment and medicine will probably have computational biology, and our newest Nobel laureates to thank.