Full Speed Ahead
Even as his lab-and his field-takes its first steps, Knight is looking to the future. He says he isn’t concerned about the ridiculously slow speed of today’s genetic approaches to biocomputing. He and other researchers started with DNA-based systems, Knight says, because genetic engineering is relatively well understood. “You start with the easy systems and move to the hard systems.”
And there are plenty of biological systems-including systems based on nerve cells, such as our own brains-that operate faster than it’s possible to turn genes on and off, Knight says. A neuron can respond to an external stimulus, for example, in a matter of milliseconds. The downside, says Knight, is that some of the faster biological mechanisms aren’t currently understood as well as genetic functions are, and so “are substantially more difficult to manipulate and mix and match.”
ill, the Molecular Sciences Institute’s Brent believes that today’s DNA-based biocomputer prototypes are steppingstones to computers based on neurochemistry. “Thirty years from now we will be using our knowledge of developmental neurobiology to grow appropriate circuits that will be made out of nerve cells and will process information like crazy,” Brent predicts. Meanwhile, pioneers like Knight, Collins, Gardner and Elowitz will continue to produce new devices unlike anything that ever came out of a microprocessor factory, and to lay the foundations for a new era of computing.
Who’s Who in Biocomputing Organization Key Researcher Focus Lawrence Berkeley National Laboratory Adam Arkin Genetic circuits and circuit addressing Boston University James J. Collins Genetic applets Rockefeller University Michael Elowitz Genetic circuits MIT Thomas F. Knight Amorphous computing