Treatments based on molecular computers are still some way off. Today’s most elaborate DNA circuits operate on work benches, not inside cells. But the border between computing and biology is vanishing fast, and the process of hijacking the information-processing potential of DNA to build logic circuits has only just begun.
For a drastic innovation [of current computer technologies], it was suggested already a long time ago that the basic components should go to the molecular level. The result would be smaller than anything we can make with present technology. Quantum computing and DNA computing are two recent manifestations of that suggestion.
DNA computation has emerged in the last ten years as an exciting new research field at the intersection (and, some would say, frontiers) of computer science, biology, engineering, and mathematics. Although anticipated by Feynman as long ago as the 1950s, the notion of performing computations at a molecular level was only realized in 1994, with Adleman's seminal work on computing with DNA.
Unlike silicon chips, however, DNA-based computers could be made small enough to operate inside cells and control their activity. "If you can programme events at a molecular level in cells, you can cure or kill cells which are sick or in trouble and leave the other ones intact. You cannot do this with electronics,” says Luca Cardelli of Microsoft’s research centre in Cambridge, England, where the software giant is developing tools for designing molecular circuits.
DNA computation may outstrip modern silicon computers on three counts:
1. Speed. This should fall out from the massive parallelism of the approach, amortized across the slow serial operations.
2. Energy efficiency. Since the molecules actually release energy when they anneal together, there is some hope that computations could be carried out using very little energy.
3. Information density. Packing 10^20 strands of data into a liter of volume would give us an information density at least five orders of magnitude better than current hard drive technology.
But, the big question on everyone's minds was whether or not DNA computation is universal. That is, is it possible to construct a DNA computer that can compute any given (computable) function? In short, yes.
Things are dramatically different if only an error rate of 0.01 is attainable. The figures tell us quite clearly where the borderline of the feasibility of DNA computing lies, at least in the case where the task is particularly suitable for DNA computing, as we have already observed cryptanalytic tasks to be. An error rate of 0.01, let alone an even bigger error rate, would make DNA computing definitely unfeasible.
In any DNA computational procedure, the main challenge is to encode each object of interest into a DNA sequence. A correct design is essential in order to ensure optimal results; an incorrect design could result in wrong sequences following the ligation process.
Leonard Adleman ... the University of Southern California computer scientist and world-famous cryptographer who invented the field of DNA computing confesses that "DNA computers are unlikely to become stand-alone competitors for electronic computers." He continues, somewhat apologetically: "We simply cannot, at this time, control molecules with the deftness that electrical engineers and physicists control electrons."
As Adleman now sees it, DNA computing is a field that's less about beating silicon than about surprising new combinations of biology and computer science that are pushing the limits in both fields-sometimes in unexpected directions. Scientists are still working hard on ways to tap the awesome number-crunching abilities of DNA for specialized types of applications, such as code breaking. But beyond that, the innate intelligence built into DNA molecules could help fabricate tiny, complex structures-in essence using computer logic not to crunch numbers but to build things.