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Here is the INFO on DNA Analyzing Chips

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DNA Computing
by Mike Wisz

In a test tube somewhere at a lab in USC, one-fiftieth of a teaspoon of DNA chugged away at a problem, perhaps the first ancestor of a future generation of computers that will leave today's supercomputers in the dust. This past November, Dr. Leonard Adleman found a way to exploit the speed and efficiency the biological reactions to solve the "Hamiltonian path problem," also known as the "traveling salesman problem." His DNA computing experiment has been heralded as the "first example of true nanotechnology", and even the "start of a new era," forging an unprecedented link between computational science and life science.

DNA Computing
by Mike Wisz

In a test tube somewhere at a lab in USC, one-fiftieth of a teaspoon of DNA chugged away at a problem, perhaps the first ancestor of a future generation of computers that will leave today's supercomputers in the dust. This past November, Dr. Leonard Adleman found a way to exploit the speed and efficiency the biological reactions to solve the "Hamiltonian path problem," also known as the "traveling salesman problem." His DNA computing experiment has been heralded as the "first example of true nanotechnology", and even the "start of a new era," forging an unprecedented link between computational science and life science


Adleman used well-established techniques of molecular biology to weed out the Hamiltonian path, the one that entered all vertices, starting at one and ending at six. After generating the numerous random paths in the first step, he used polymerase chain reaction (PCR) to amplify and keep only the paths that began on vertex 1 and ended at vertex 6. The next two steps kept only those strands that passed through six vertices, entering each vertex at least once. At this point, any paths that remained would code for a Hamiltonian path, thus solving the problem.

Although Adleman admits that he is unsure how to proceed for paths much larger than six vertices, the power of molecular computers is still worth comparing to today's systems. In speed, the DNA clearly wins the race, performing 1,000 operations per second more than the fastest supercomputers (which execute about 1012 operations per second). To get a better idea of the speed, consider that a typical desktop computer performs a thousand million times slower than the DNA, a measly 106 operations per second!

In energy efficiency, a biological system such as a cell can perform 2x1019 power operations using one joule of energy (the amount of energy needed to burn a 100-watt light bulb for a second), while a supercomputer only manages 1010 operations, making it 1010 less energy efficient! Just as the cell pushes the limit of the second law of thermodynamics, which predicts that one joule can fuel a maximum of 34x1019 irreversible power operations, the DNA computer's energy consumption from DNA strand synthesis and PCR should also be small compared to that used up by a supercomputer.

The potential for information storage in molecular computers follows the same trend as speed and efficiency. While storage media of today, such as videotapes, store information at a density of one bit per 1012 cubic nanometers, the molecules of DNA make this figure seem ridiculous, with an information storage density of 1 bit per cubic nanometer - a trillion times less space!

Even though Adleman's molecular computer would have a hard time multiplying two 100-digit integers, an easy task for one of today's electronic computers, its capability to solve complex problems is unparalleled. However, as work continues in this exciting area, molecular computers may impress us once again and challenge the dominance of electronic systems in solving even more types of problems. After all, the DNA based system of computation has had millions of years to evolve and perfect itself, while man-made systems have only existed for a small fraction of this span. It is an impressive computer indeed that can spend eons producing new and varied organisms through trial and error until it finally finds a solution - the intelligent species we call human beings. The computers of tomorrow are on the threshold.

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Thats all I have to say about that.....

- Noia