h a l f b a k e r yWe have a low common denominator: 2
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We can solve NP complete problems with regular computers, too. "NP complete" just means that (with any algorithm known to date) we can't solve the algorithm in polynomial time; for an input of size N, it will take (at least) O(2^N) steps to solve the problem. |
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DNA computers don't bring anything special to the table; they're just a form of massively parallel molecular computation. So, yes, we can certainly simulate them, and thereby "solve NP problems", but the whole point of using a DNA computer in the first place would be to do so relatively quickly, and the simulation would of course run no faster than the host computer. |
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I don't know if the proof of this would stand up to grey number concatenation and analysis of the computing resources used, but DNA lends itself to evaluation of its stucture by digital knot deformation. If a bioaddressor was to be introduced to the culture medium, its substrate could be made verifiable by 2-D scanning technology. Knowing the way things respond to alteration in their structure could enable a gene designer to set up scenarios for 'the lost sheep' or 'design for a possible sinkhole' |
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As a genetic engineer, I second that 'What?' |
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