It has been tried before, but researchers are now fully realizing the potential of DNA and want to create a programmable way of combining computers with chemistry. As said one the leading researchers at CalTech, 'Programming chemical systems needs to be thought about. The meeting of computer science and chemistry hasn't happened yet, but is right around the corner. There's nothing logically, chemically or physically impossible about computing with molecular systems.' Another researcher from the University of Washington added that 'if we understand the language, we could develop a biological response through reprogramming, no different than a remedy pushed out by Norton AntiVirus on a computer.' The same researcher said something that might one day become history. "The 20th century was the age of information. The 21st century is going to be the age of life." But read more...
This research project has been led by Erik Winfree, a professor of computer science at the California Institute of Technology. He was helped by other members of the DNA and Natural Algorithms Group including David Yu Zhang, a graduate student.
Here are some quotes from the article published by The Daily of the University of Washington about this research. "'Programming in a DNA world offers a variety of applications,' said Winfree, speaking at a computer science and engineering colloquium Tuesday. 'We can design a range of structures capable of creating complex patterns, circuits, and motors.' Winfree's research group has produced research that created patterns and structures out of DNA in test tubes. Shapes such as squares, stars and smiley faces were obtained by programming DNA sequences. The sequences are passed into a strand of DNA that is heated and cooled, causing it to self-assemble into the prescribed shape. The chemistry and methods are efficient, producing correctly formed molecules 60 to 90 percent of the time.
As you can infer from the numbers above, reliability is one of the key challenges that this future way of computing is facing. "'Right now we can build new devices with roughly ten components,' said [Eric Klavins, an assistant professor of electrical engineering at the University of Washington working at the Self-Organizing Systems Lab]. 'The questions that remain involve how to scale that number up and how to build in robustness. We need to experiment with new contexts.' Computing is an abstract notion. It can be done on a multitude of scales by a number of methods. Life is fully capable of addressing these complexities. Klavins said that if scientists understand the manner in which such computing operates, it will mark a revolution in science."
This research work has been published in Science under the name "Engineering Entropy-Driven Reactions and Networks Catalyzed by DNA" (Volume 318, Issue 5853, Pages 1121-1125, November 16, 2007). Here is how Science's introduction to the article. "Biochemical circuits based on nucleic acids can use output strands of oligonucleotides as catalysts for subsequent reactions to amplify small signals for use in sensors."
Here is the beginning of the abstract. "Artificial biochemical circuits are likely to play as large a role in biological engineering as electrical circuits have played in the engineering of electromechanical devices. Toward that end, nucleic acids provide a designable substrate for the regulation of biochemical reactions. However, it has been difficult to incorporate signal amplification components. We introduce a design strategy that allows a specified input oligonucleotide to catalyze the release of a specified output oligonucleotide, which in turn can serve as a catalyst for other reactions."
This scientific paper has been abundantly commented in the media. Here are two links to articles published in New Scientist, "Molecular 'amplifier' boosts DNA computing" (Anil Ananthaswamy, November 15, 2007) and in The Scientist, "A programming language for DNA" (Melissa Lee Phillips, November 15, 2007).
The Caltech DNA and Natural Algorithms Group also wrote about the paper published in Science in its list of publications. And frankly, I enjoyed the tone of this introduction which mixes humor and science. "The entropy of the universe is always increasing. That sounds like a force -- something that keeps increasing can push something else, can't it? The problem, of course, is that using entropy to do work sounds like trying to plow a field by herding stray cats -- it just ends in chaos. But does it have to? Nope: chemists, in fact, are quite familiar with entropy-driven reactions. In this paper, we show how to design systems of DNA molecules with catalytic reactions that are driven by entropy. And it doesn't end in chaos, far from it: we argue that our reactions can be wired together into arbitrary analog or digital circuits, which means they can process information and thus create order. So entropy can drive the production of order? Yup. No wonder the universe is such a beautiful place!"
The same team published on September 19, 2007 a technical report called "Computation with Finite Stochastic Chemical Reaction Networks." Here is their introduction. "Some people think of chemistry as a bag of colored marbles. Shake really hard. When the marbles hit each other, they change colors, according to rules. So there's a bit of structure, but it's a chaotic mess -- at any given moment, it's anyone's guess what will happen next. Can chemistry do computation, then? [...] What we show here is that finite stochastic chemical reaction networks -- bags of marbles without strings -- can also perform Turing-universal computation. Reasonably quickly, too! This result holds if we accept some probability, no matter how small, that the chemistry will produce the wrong output... but remarkably, the result fails if we insist that the chemistry always and without exception produces the correct output. It pays to be tolerant, if even ever so slightly."
It's very refreshing to see scientists commenting their works in plain English. You can compare what the scientists wrote with the abstract of their technical report (PDF format, 21 pages, 527 KB). What is the introduction which is the easiest to understand? Drop me a note if you think that the official abstract is clearer.
Sources: Brian Smoliak, The Daily, University of Washington, November 16, 2007; and various websites
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