DNA computing: Difference between revisions

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By default, the computer is considered to have played first in the central square. The human player starts with eight different types of DNA strands corresponding to the eight remaining boxes that may be played. To play box number i, the human player pours into all bins the strands corresponding to input #i. These strands bind to certain DNA enzymes present in the bins, resulting, in one of these bins, in the deformation of the DNA enzymes which binds to the substrate and cuts it. The corresponding bin becomes fluorescent, indicating which box is being played by the DNA computer. The DNA enzymes are divided among the bins in such a way as to ensure that the best the human player can achieve is a draw, as in real tic-tac-toe.
 
=== Neural network based computing ===
Kevin Cherry and [[Lulu Qian]] at Caltech developed a DNA-based artificial neural network that can recognize 100-bit hand-written digits. They achieve this by programming on computer in advance with appropriate set of weights represented by varying concentrations weight molecules which will later be added to the test tube that holds the input DNA strands.<ref>{{Cite journal|last1=Qian|first1=Lulu|last2=Winfree|first2=Erik|last3=Bruck|first3=Jehoshua|date=July 2011|title=Neural network computation with DNA strand displacement cascades|journal=Nature|language=En|volume=475|issue=7356|pages=368–372|doi=10.1038/nature10262|pmid=21776082|s2cid=1735584|issn=0028-0836}}</ref><ref name=":4">{{Cite journal|last1=Cherry|first1=Kevin M.|last2=Qian|first2=Lulu|date=2018-07-04|title=Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks|journal=Nature|language=En|volume=559|issue=7714|pages=370–376|doi=10.1038/s41586-018-0289-6|pmid=29973727|issn=0028-0836|bibcode=2018Natur.559..370C|s2cid=49566504|url=https://authors.library.caltech.edu/84840/}}</ref>
 
=== Improved speed with Localized (cache-like) Computing ===
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=== Toehold exchange ===
Besides simple strand displacement schemes, DNA computers have also been constructed using the concept of toehold exchange.<ref name=":4">{{Cite journal |last1=Cherry |first1=Kevin M. |last2=Qian |first2=Lulu |date=2018-07-04 |title=Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks |url=https://authors.library.caltech.edu/84840/ |journal=Nature |language=En |volume=559 |issue=7714 |pages=370–376 |bibcode=2018Natur.559..370C |doi=10.1038/s41586-018-0289-6 |issn=0028-0836 |pmid=29973727 |s2cid=49566504}}</ref> In this system, an input DNA strand binds to a [[sticky end]], or toehold, on another DNA molecule, which allows it to displace another strand segment from the molecule. This allows the creation of modular logic components such as AND, OR, and NOT gates and signal amplifiers, which can be linked into arbitrarily large computers. This class of DNA computers does not require enzymes or any chemical capability of the DNA.<ref>{{Cite journal|last1=Seelig|first1=G.|last2=Soloveichik|first2=D.|last3=Zhang|first3=D. Y.|last4=Winfree|first4=E.|s2cid=10966324|date=8 December 2006|title=Enzyme-free nucleic acid logic circuits|journal=Science|volume=314|issue=5805|pages=1585–1588|bibcode=2006Sci...314.1585S|doi=10.1126/science.1132493|pmid=17158324|url=https://authors.library.caltech.edu/22753/2/DNA_logic_circuits2006_supp.pdf}}</ref>
 
=== Chemical reaction networks (CRNs) ===