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complete. While newer ways with external enzyme sources are reporting faster and more compact circuits, Chatterjee et al. demonstrated an interesting idea in the field to speed up computation through localized DNA circuits, a concept being further explored by other groups. This idea, while originally proposed in the field of computer architecture, has been adopted in this field as well. In computer architecture, it is very well-known that if the instructions are executed in sequence, having them loaded in the cache will inevitably lead to fast performance, also called the principle of localization. This is because with instructions in fast cache memory, there is no need swap them in and out of main memory, which can be slow. Similarly, in
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444:, which itself is a tumor suppressor. On negative diagnosis it was decided to release a suppressor of the positive diagnosis drug instead of doing nothing. A limitation of this implementation is that two separate automata are required, one to administer each drug. The entire process of evaluation until drug release took around an hour to complete. This method also requires transition molecules as well as the FokI enzyme to be present. The requirement for the FokI enzyme limits application
105:
required in
Adleman's implementation would grow exponentially. Therefore, computer scientists and biochemists started exploring tile-assembly where the goal was to use a small set of DNA strands as tiles to perform arbitrary computations upon growth. Other avenues that were theoretically explored in the late 90's include DNA-based security and cryptography, computational capacity of DNA systems, DNA memories and disks, and DNA-based robotics.
148:. Within seconds, the small fragments form bigger ones, representing the different travel routes. Through a chemical reaction, the DNA fragments representing the longer routes were eliminated. The remains are the solution to the problem, but overall, the experiment lasted a week. However, current technical limitations prevent the evaluation of the results. Therefore, the experiment isn't suitable for the application, but it is nevertheless a
205:
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.
320:, 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.
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limit. The amount of fluorescence can then be measured to tell whether or not a reaction took place. The DNAzyme that changes is then "used", and cannot initiate any more reactions. Because of this, these reactions take place in a device such as a continuous stirred-tank reactor, where old product is removed and new molecules added.
558:
The slow processing speed of a DNA computer (the response time is measured in minutes, hours or days, rather than milliseconds) is compensated by its potential to make a high amount of multiple parallel computations. This allows the system to take a similar amount of time for a complex calculation as
20:
510:
in that it takes advantage of the many different molecules of DNA to try many different possibilities at once. For certain specialized problems, DNA computers are faster and smaller than any other computer built so far. Furthermore, particular mathematical computations have been demonstrated to work
100:
about a decade before Len
Adleman's demonstration. Ned's original idea in the 1980s was to build arbitrary structures using bottom-up DNA self-assembly for applications in crystallography. However, it morphed into the field of structural DNA self-assembly which as of 2020 is extremely sophisticated.
84:
Since then the field has expanded into several avenues. In 1995, the idea for DNA-based memory was proposed by Eric Baum who conjectured that a vast amount of data can be stored in a tiny amount of DNA due to its ultra-high density. This expanded the horizon of DNA computing into the realm of memory
204:
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
196:
against a human player. The calculator consists of nine bins corresponding to the nine squares of the game. Each bin contains a substrate and various combinations of DNA enzymes. The substrate itself is composed of a DNA strand onto which was grafted a fluorescent chemical group at one end, and the
226:
One of the challenges of DNA computing is its speed. While DNA as a substrate is biologically compatible i.e. it can be used at places where silicon technology cannot, its computation speed is still very slow. For example, the square-root circuit used as a benchmark in field took over 100 hours to
217:
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
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The DNAzyme logic gate changes its structure when it binds to a matching oligonucleotide and the fluorogenic substrate it is bonded to is cleaved free. While other materials can be used, most models use a fluorescence-based substrate because it is very easy to detect, even at the single molecule
104:
In 1994, Prof. Seeman's group demonstrated early DNA lattice structures using a small set of DNA components. While the demonstration by
Adleman showed the possibility of DNA-based computers, the DNA design was trivial because as the number of nodes in a graph grows, the number of DNA components
263:
for implementing reversible gates and circuits on DNA computers by combining DNA computing and reversible computing techniques. This paper also proposes a universal reversible gate library (URGL) for synthesizing n-bit reversible circuits on DNA computers with an average length and cost of the
255:
and his group at Duke
University have proposed two different techniques to reuse the computing DNA complexes. The first design uses dsDNA gates, while the second design uses DNA hairpin complexes. While both the designs face some issues (such as reaction leaks), this appears to represent a
373:
machines, respectively; Stojanovic has also demonstrated logic gates using the 8-17 DNAzyme. While these DNAzymes have been demonstrated to be useful for constructing logic gates, they are limited by the need for a metal cofactor to function, such as Zn or Mn, and thus are not useful
119:
first demonstrated the idea of a DNA-based walker that traversed along a track similar to a line follower robot. They used molecular biology as a source of energy for the walker. Since this first demonstration, a wide variety of DNA-based walkers have been demonstrated.
336:
showed that DNA can be used as a substrate to implement arbitrary chemical reactions. This opened the way to design and synthesis of biochemical controllers since the expressive power of CRNs is equivalent to a Turing machine. Such controllers can potentially be used
144:". For this purpose, different DNA fragments were created, each one of them representing a city that had to be visited. Every one of these fragments is capable of a linkage with the other fragments created. These DNA fragments were produced and mixed in a
231:, the DNA strands responsible for computation are fixed on a breadboard-like substrate ensuring physical proximity of the computing gates. Such localized DNA computing techniques have shown to potentially reduce the computation time by
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for a simple one. This is achieved by the fact that millions or billions of molecules interact with each other simultaneously. However, it is much harder to analyze the answers given by a DNA computer than by a digital one.
2263:
Song, Tianqi; Eshra, Abeer; Shah, Shalin; Bui, Hieu; Fu, Daniel; Yang, Ming; Mokhtar, Reem; Reif, John (2019-09-23). "Fast and compact DNA logic circuits based on single-stranded gates using strand-displacing polymerase".
782:
Organick, Lee; Ang, Siena Dumas; Chen, Yuan-Jyue; Lopez, Randolph; Yekhanin, Sergey; Makarychev, Konstantin; Racz, Miklos Z.; Kamath, Govinda; Gopalan, Parikshit; Nguyen, Bichlien; Takahashi, Christopher N. (March 2018).
518:, the study of which problems are computationally solvable using different models of computation. For example, if the space required for the solution of a problem grows exponentially with the size of the problem (
357:. These DNAzymes are used to build logic gates analogous to digital logic in silicon; however, DNAzymes are limited to 1-, 2-, and 3-input gates with no current implementation for evaluating statements in series.
385:, consisting of a single strand of DNA which has a loop at an end, are a dynamic structure that opens and closes when a piece of DNA bonds to the loop part. This effect has been exploited to create several
1715:
Ong, Luvena L.; Hanikel, Nikita; Yaghi, Omar K.; Grun, Casey; Strauss, Maximilian T.; Bron, Patrick; Lai-Kee-Him, Josephine; Schueder, Florian; Wang, Bei; Wang, Pengfei; Kishi, Jocelyn Y. (December 2017).
364:
Two commonly used DNAzymes are named E6 and 8-17. These are popular because they allow cleaving of a substrate in any arbitrary location. Stojanovic and MacDonald have used the E6 DNAzymes to build the
3508:— The book starts with an introduction to DNA-related matters, the basics of biochemistry and language and computation theory, and progresses to the advanced mathematical theory of DNA computing.
2876:
MacDonald, J.; Li, Y.; Sutovic, M.; Lederman, H.; Pendri, K.; Lu, W.; Andrews, B. L.; Stefanovic, D.; Stojanovic, M. N. (2006). "Medium Scale
Integration of Molecular Logic Gates in an Automaton".
50:. Research and development in this area concerns theory, experiments, and applications of DNA computing. Although the field originally started with the demonstration of a computing application by
546:" production. A Caltech group is working on the manufacturing of these nucleic-acid-based integrated circuits. One of these chips can compute whole square roots. A compiler has been written in
328:
The full stack for DNA computing looks very similar to a traditional computer architecture. At the highest level, a C-like general purpose programming language is expressed using a set of
54:
in 1994, it has now been expanded to several other avenues such as the development of storage technologies, nanoscale imaging modalities, synthetic controllers and reaction networks, etc.
436:. Their automata evaluated the expression of each gene, one gene at a time, and on positive diagnosis then released a single strand DNA molecule (ssDNA) that is an antisense for
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DNA nanotechnology has been applied to the related field of DNA computing. DNA tiles can be designed to contain multiple sticky ends with sequences chosen so that they act as
2323:
Chatterjee, Gourab; Dalchau, Neil; Muscat, Richard A.; Phillips, Andrew; Seelig, Georg (2017-07-24). "A spatially localized architecture for fast and modular DNA computing".
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The most fundamental operation in DNA computing and molecular programming is the strand displacement mechanism. Currently, there are two ways to perform strand displacement:
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316:
Besides simple strand displacement schemes, DNA computers have also been constructed using the concept of toehold exchange. In this system, an input DNA strand binds to a
526:, it still grows exponentially with the size of the problem on DNA machines. For very large EXPSPACE problems, the amount of DNA required is too large to be practical.
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There are multiple methods for building a computing device based on DNA, each with its own advantages and disadvantages. Most of these build the basic logic gates (
2578:
Goel, Ashish; Ibrahimi, Morteza (2009). "Renewable, Time-Responsive DNA Logic Gates for
Scalable Digital Circuits". In Deaton, Russell; Suyama, Akira (eds.).
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Bui, Hieu; Shah, Shalin; Mokhtar, Reem; Song, Tianqi; Garg, Sudhanshu; Reif, John (2018-01-25). "Localized DNA Hybridization Chain
Reactions on DNA Origami".
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Yin, Peng; Yan, Hao; Daniell, Xiaoju G.; Turberfield, Andrew J.; Reif, John H. (2004). "A Unidirectional DNA Walker That Moves
Autonomously along a Track".
1997:
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Jungmann, Ralf; Avendaño, Maier S.; Dai, Mingjie; Woehrstein, Johannes B.; Agasti, Sarit S.; Feiger, Zachary; Rodal, Avital; Yin, Peng (May 2016).
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448:, at least for use in "cells of higher organisms". It should also be pointed out that the 'software' molecules can be reused in this case.
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Self-assembled structure from a few nanometers tall all the way up to several tens of micrometers in size have been demonstrated in 2018.
1084:
Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg (October 2013).
332:. This intermediate representation gets translated to domain-level DNA design and then implemented using a set of DNA strands. In 2010,
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498:. This shows that computation can be incorporated into the assembly of DNA arrays, increasing its scope beyond simple periodic arrays.
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significant breakthrough in the field of DNA computing. Some other groups have also attempted to address the gate reusability problem.
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other end, a repressor group. Fluorescence is only active if the molecules of the substrate are cut in half. The DNA enzymes simulate
2911:
838:
Shah, Shalin; Dubey, Abhishek K.; Reif, John (2019-04-10). "Programming
Temporal DNA Barcodes for Single-Molecule Fingerprinting".
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201:. For example, such a DNA will unfold if two specific types of DNA strand are introduced to reproduce the logic function AND.
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Qian, Lulu; Winfree, Erik; Bruck, Jehoshua (July 2011). "Neural network computation with DNA strand displacement cascades".
1403:
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Kahan, M.; Gil, B.; Adar, R.; Shapiro, E. (2008). "Towards molecular computers that operate in a biological environment".
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3570:
3453:
1030:; Chen, Yuan-Jyue; Reif, John (2020-05-04). "Using Strand Displacing Polymerase To Program Chemical Reaction Networks".
252:
66:
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Qian, L.; Winfree, E. (2011-06-02). "Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades".
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Bond, G. L.; Hu, W.; Levine, A. J. (2005). "MDM2 is a Central Node in the p53 Pathway: 12 Years and Counting".
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was a test tube filled with 100 microliters of a DNA solution. He managed to solve an instance of the directed
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showed that the DNA operations performed by genetic recombination in some organisms are Turing complete.
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2531:"Renewable DNA seesaw logic circuits enabled by photoregulation of toehold-mediated strand displacement"
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problem. In Adleman's experiment, the Hamiltonian Path Problem was implemented notationally as the "
2582:. Lecture Notes in Computer Science. Vol. 5877. Berlin, Heidelberg: Springer. pp. 67–77.
2018:
Braich, Ravinderjit S., et al. "Solution of a satisfiability problem on a gel-based DNA computer."
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Srinivas, Niranjan; Parkin, James; Seelig, Georg; Winfree, Erik; Soloveichik, David (2017-12-15).
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or DNAzyme) catalyze a reaction when interacting with the appropriate input, such as a matching
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247:, bringing the technology one step closer to the silicon-based computing used in (for example)
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Eshra, A.; Shah, S.; Song, T.; Reif, J. (2019). "Renewable DNA hairpin-based logic circuits".
1718:"Programmable self-assembly of three-dimensional nanostructures from 10,000 unique components"
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409:; there is analogous hardware, in the form of an enzyme, and software, in the form of DNA.
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In 2002, J. Macdonald, D. Stefanović and M. Stojanović created a DNA computer able to play
47:
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Garg, Sudhanshu; Shah, Shalin; Bui, Hieu; Song, Tianqi; Mokhtar, Reem; Reif, John (2018).
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Bancroft, Carter; Bowler, Timothy; Bloom, Brian; Clelland, Catherine Taylor (2001-09-07).
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enzyme and expanded on their work by going on to show automata that diagnose and react to
8:
2140:"Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks"
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Stojanovic, M. N.; Stefanovic, D. (2003). "A deoxyribozyme-based molecular automaton".
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Adleman, L. M. (1994). "Molecular computation of solutions to combinatorial problems".
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Using strand displacement reactions (SRDs), reversible proposals are presented in the
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Benenson, Y.; Paz-Elizur, T.; Adar, R.; Keinan, E.; Livneh, Z.; Shapiro, E. (2001).
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Leier, André; Richter, Christoph; Banzhaf, Wolfgang; Rauhe, Hilmar (2000-06-01).
1591:"Fractal assembly of micrometre-scale DNA origami arrays with arbitrary patterns"
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899:"Wide-field subdiffraction imaging by accumulated binding of diffusing probes"
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1975:
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1315:— The first DNA computing paper. Describes a solution for the directed
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on their surfaces. Click the image for further details. Image from Rothemund
350:
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Zoja Ignatova; Israel Martinez-Perez; Karl-Heinz Zimmermann (January 2008).
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Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades
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Benenson, Shapiro and colleagues have demonstrated a DNA computer using the
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The field of DNA computing can be categorized as a sub-field of the broader
77:. Since the initial Adleman experiments, advances have occurred and various
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DNA computing does not provide any new capabilities from the standpoint of
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260:
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Seelig, G.; Soloveichik, D.; Zhang, D. Y.; Winfree, E. (8 December 2006).
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3182:"An autonomous molecular computer for logical control of gene expression"
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Seeman, Nadrian C. (1982-11-21). "Nucleic acid junctions and lattices".
3230:
An autonomous molecular computer for logical control of gene expression
2992:
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1652:
Wagenbauer, Klaus F.; Sigl, Christian; Dietz, Hendrik (December 2017).
981:
433:
386:
333:
317:
277:
221:
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Weiss, S. (1999). "Fluorescence Spectroscopy of Single Biomolecules".
389:. These logic gates have been used to create the computers MAYA I and
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479:
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19:
3115:"Programmable and autonomous computing machine made of biomolecules"
3051:"A Mechanical Turing Machine: Blueprint for a Biomolecular Computer"
2843:
2482:
1589:
Tikhomirov, Grigory; Petersen, Philip; Qian, Lulu (December 2017).
720:
543:
519:
116:
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Benenson, Y.; Gil, B.; Ben-Dor, U.; Adar, R.; Shapiro, E. (2004).
2966:"Dinucleotide Junction Cleavage Versatility of 8-17 Deoxyribozyme"
721:"DNA Fountain enables a robust and efficient storage architecture"
261:"Synthesis Strategy of Reversible Circuits on DNA Computers" paper
123:
97:
539:
491:
390:
375:
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73:
use of DNA as a form of computation which solved the seven-point
3597:
International Meeting on DNA Computing and Molecular Programming
3596:
2529:
Song, Xin; Eshra, Abeer; Dwyer, Chris; Reif, John (2017-05-25).
1836:
Guarnieri, Frank; Fliss, Makiko; Bancroft, Carter (1996-07-12).
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from a DNA basis. Some of the different bases include DNAzymes,
2322:
1204:
Soloveichik, David; Seelig, Georg; Winfree, Erik (2010-03-23).
421:
405:
Enzyme-based DNA computers are usually of the form of a simple
69:
initially developed this field in 1994. Adleman demonstrated a
23:
The biocompatible computing device: Deoxyribonucleic acid (DNA)
1469:, a hard-on-average NP-complete problem. Also available here:
2651:
1483:"Building an associative memory vastly larger than the brain"
1366:
Boneh, D.; Dunworth, C.; Lipton, R. J.; Sgall, J. ĂŤ. (1996).
963:
482:. A DX array has been demonstrated whose assembly encodes an
425:
3112:
2921:
2613:"Synthesis Strategy of Reversible Circuits on DNA Computers"
1443:"Using DNA to solve the Bounded Post Correspondence Problem"
2922:
Stojanovic, M. N.; Mitchell, T. E.; Stefanovic, D. (2002).
1898:
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MAYA II, a second-generation tic-tac-toe playing automaton
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238:
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535:
441:
35:
3470:— The first general text to cover the whole field.
3319:
Rothemund, P. W. K.; Papadakis, N.; Winfree, E. (2004).
1953:
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for applications such as preventing hormonal imbalance.
3321:"Algorithmic Self-Assembly of DNA Sierpinski Triangles"
897:
Sharonov, Alexey; Hochstrasser, Robin M. (2006-12-12).
264:
constructed circuits better than the previous methods.
3592:
Japanese Researchers store information in bacteria DNA
3587:
Bringing DNA computers to life, in Scientific American
3582:- The New York Times DNA Computer for detecting Cancer
3179:
1835:
1588:
1026:
Shah, Shalin; Wee, Jasmine; Song, Tianqi; Ceze, Luis;
3314:
3312:
132:
presented the first prototype of a DNA computer. The
3532:— A new general text to cover the whole field.
2829:
1654:"Gigadalton-scale shape-programmable DNA assemblies"
1206:"DNA as a universal substrate for chemical kinetics"
896:
781:
656:"Next-Generation Digital Information Storage in DNA"
486:
operation; this allows the DNA array to implement a
323:
222:
Improved speed with Localized (cache-like) Computing
3277:
1714:
1651:
966:"Quantitative super-resolution imaging with qPAINT"
3309:
2757:http://www.lps.ens.fr/~vincent/smb/PDF/weiss-1.pdf
2528:
2373:
243:Subsequent research on DNA computing has produced
3559:. In: Die Neue Gesellschaft / Frankfurter Hefte
2465:
2068:Des assemblages d'ADN rompus au jeu et au travail
2032:Adleman, Leonard M (1998). "Computing with DNA".
1998:"Biocomputing researcher awarded the Bucke Prize"
1086:"Programmable chemical controllers made from DNA"
654:Church, G. M.; Gao, Y.; Kosuri, S. (2012-08-16).
295:
208:
160:First results to these problems were obtained by
3608:
2262:
2083:
2066:- J. Macdonald, D. Stefanovic et M. Stojanovic,
1441:Lila Kari; Greg Gloor; Sheng Yu (January 2000).
460:DNA arrays that display a representation of the
89:demonstrations were made almost after a decade.
2964:Cruz, R. P. G.; Withers, J. B.; Li, Y. (2004).
2774:Proceedings of the National Academy of Sciences
2416:
1210:Proceedings of the National Academy of Sciences
1025:
903:Proceedings of the National Academy of Sciences
785:"Random access in large-scale DNA data storage"
718:
653:
124:Applications, examples, and recent developments
3173:
3602:LiveScience.com-How DNA Could Power Computers
2963:
837:
719:Erlich, Yaniv; Zielinski, Dina (2017-03-02).
474:DNA nanotechnology: Algorithmic self-assembly
3502:: CS1 maint: multiple names: authors list (
3455:Theoretical and Experimental DNA Computation
3240:
2767:
2610:
2577:
1154:"Enzyme-free nucleic acid dynamical systems"
451:
3448:
2770:"A general purpose RNA-cleaving DNA enzyme"
2203:
2138:Cherry, Kevin M.; Qian, Lulu (2018-07-04).
2074:, No. 375, January 2009, p. 68-75
529:
304:Toehold mediated strand displacement (TMSD)
2611:Rofail, Mirna; Younes, Ahmed (July 2021).
2137:
2022:. Springer Berlin Heidelberg, 2001. 27-42.
307:Polymerase-based strand displacement (PSD)
16:Computing using molecular biology hardware
3346:
3336:
3213:
3146:
3078:
2991:
2981:
2803:
2793:
2654:"Enzyme-free nucleic acid logic circuits"
2636:
2554:
2481:
2434:
1901:"Long-Term Storage of Information in DNA"
1757:
1506:
1458:
1383:
1292:
1247:
1229:
1169:
1125:
997:
940:
922:
679:
155:
2928:Journal of the American Chemical Society
2708:
2706:
2419:"Renewable Time-Responsive DNA Circuits"
1032:Journal of the American Chemical Society
455:
18:
3480:DNA Computing - New Computing Paradigms
3271:
3106:
3045:
2580:DNA Computing and Molecular Programming
2031:
1956:Angewandte Chemie International Edition
1465:— Describes a solution for the bounded
1270:
239:Renewable (or reversible) DNA computing
3609:
3458:. Natural Computing Series. Springer.
3372:Computing in Science & Engineering
3370:Lewin, D. I. (2002). "DNA computing".
1783:"Cryptography with DNA binary strands"
1537:
1426:: CS1 maint: archived copy as title (
1351:: CS1 maint: archived copy as title (
81:have been proven to be constructible.
3567:, Heft 2/96, Februar 1996, S. 170–172
3369:
2768:Santoro, S. W.; Joyce, G. F. (1997).
2712:
2703:
2199:
2197:
2133:
2131:
1990:
1390:— Describes a solution for the
1199:
1197:
46:hardware, instead of the traditional
1480:
1147:
1145:
1079:
1077:
1021:
1019:
1017:
2469:IEEE Transactions on Nanotechnology
1947:
1368:"On the computational power of DNA"
1264:
542:was established in 2009 aiming at "
311:
187:
13:
3474:Gheorge Paun, Grzegorz Rozenberg,
3441:
2367:
2256:
2194:
2128:
1194:
14:
3653:
3537:
2924:"Deoxyribozyme-Based Logic Gates"
2054:10.1038/scientificamerican0898-54
1142:
1074:
1014:
957:
647:
330:chemical reaction networks (CRNs)
324:Chemical reaction networks (CRNs)
292:, enzymes, and toehold exchange.
67:University of Southern California
553:
420:: under expression of the genes
3427:
3416:
3398:
3363:
3234:
3039:
3008:
2957:
2915:
2869:
2823:
2761:
2645:
2604:
2571:
2522:
2459:
2410:
2316:
2077:
2060:
2025:
2012:
1892:
1829:
1774:
1708:
1645:
1582:
1531:
1474:
1434:
1359:
501:
3556:DNS – Ein neuer Supercomputer?
3280:Physica D: Nonlinear Phenomena
2983:10.1016/j.chembiol.2003.12.012
1917:10.1126/science.293.5536.1763c
1540:Journal of Theoretical Biology
1392:Boolean satisfiability problem
890:
831:
775:
712:
296:Strand displacement mechanisms
209:Neural network based computing
1:
3063:Weizmann Institute of Science
2735:10.1126/science.283.5408.1676
2006:University of Western Ontario
1807:10.1016/S0303-2647(00)00083-6
1460:10.1016/s0304-3975(99)00100-0
1385:10.1016/S0166-218X(96)00058-3
641:
218:holds the input DNA strands.
3338:10.1371/journal.pbio.0020424
1862:10.1126/science.273.5272.220
1560:10.1016/0022-5193(82)90002-9
1447:Theoretical Computer Science
1372:Discrete Applied Mathematics
860:10.1021/acs.nanolett.9b00590
7:
3549:How Stuff Works explanation
3300:10.1016/j.physd.2008.01.027
3244:Current Cancer Drug Targets
2588:10.1007/978-3-642-10604-0_7
1467:Post correspondence problem
562:
506:DNA computing is a form of
344:
142:travelling salesman problem
10:
3658:
3571:'DNA computer' cracks code
3014:Darko Stefanovic's Group,
2500:10.1109/TNANO.2019.2896189
1481:Baum, E. B. (1995-04-28).
471:
428:and an over expression of
400:
267:
183:problem with 20 variables.
172:in a graph with 7 summits.
57:
3520:. Springer. p. 288.
3410:October 14, 2011, at the
2286:10.1038/s41565-019-0544-5
2164:10.1038/s41586-018-0289-6
452:Algorithmic self-assembly
440:. MDM2 is a repressor of
30:is an emerging branch of
3406:(Caltech's own article)
3257:10.2174/1568009053332627
1317:Hamiltonian path problem
590:DNA digital data storage
530:Alternative technologies
245:reversible DNA computing
85:technology although the
75:Hamiltonian path problem
32:unconventional computing
3304:. Also available here:
3228:. Also available here:
3161:. Also available here:
2970:Chemistry & Biology
2910:. Also available here:
2864:. Also available here:
2818:. Also available here:
2755:. Also available here:
2681:10.1126/science.1132493
2388:10.1021/acsnano.7b06699
2226:10.1126/science.1200520
1508:10.1126/science.7725109
1394:. Also available here:
1319:. Also available here:
1303:10.1126/science.7973651
1231:10.1073/pnas.0909380107
1171:10.1126/science.aal2052
924:10.1073/pnas.0609643104
745:10.1126/science.aaj2038
681:10.1126/science.1226355
229:localized DNA computing
3071:10.1098/rsfs.2011.0118
2795:10.1073/pnas.94.9.4262
2436:10.1002/smll.201801470
2345:10.1038/nnano.2017.127
1968:10.1002/anie.200460522
1110:10.1038/nnano.2013.189
534:A partnership between
469:
156:Combinatorial problems
24:
3622:Models of computation
3544:DNA modeled computing
3016:Molecular Logic Gates
2325:Nature Nanotechnology
2266:Nature Nanotechnology
1090:Nature Nanotechnology
605:Molecular electronics
585:DNA code construction
459:
290:deoxyoligonucleotides
179:problem as well as a
22:
3617:Classes of computers
3517:DNA Computing Models
2952:. Also available at
2832:Nature Biotechnology
1044:10.1021/jacs.0c02240
789:Nature Biotechnology
635:Molecular logic gate
524:von Neumann machines
516:computability theory
334:Erik Winfree's group
48:electronic computing
3642:American inventions
3482:. Springer-Verlag.
3392:10.1109/5992.998634
3384:2002CSE.....4c...5L
3292:2008PhyD..237.1165K
3206:10.1038/nature02551
3198:2004Natur.429..423B
3131:2001Natur.414..430B
2890:2006NanoL...6.2598M
2786:1997PNAS...94.4262S
2727:1999Sci...283.1676W
2721:(5408): 1676–1683.
2673:2006Sci...314.1585S
2667:(5805): 1585–1588.
2638:10.3390/sym13071242
2629:2021Symm...13.1242R
2547:2017RSCAd...728130S
2541:(45): 28130–28144.
2492:2019ITNan..18..252E
2337:2017NatNa..12..920C
2278:2019NatNa..14.1075S
2218:2011Sci...332.1196Q
2212:(6034): 1196–1201.
2156:2018Natur.559..370C
2098:10.1038/nature10262
2046:1998SciAm.279b..54A
2034:Scientific American
1911:(5536): 1763–1765.
1854:1996Sci...273..220G
1799:2000BiSys..57...13L
1742:10.1038/nature24648
1734:2017Natur.552...72O
1678:10.1038/nature24651
1670:2017Natur.552...78W
1615:10.1038/nature24655
1607:2017Natur.552...67T
1552:1982JThBi..99..237S
1499:1995Sci...268..583B
1285:1994Sci...266.1021A
1279:(5187): 1021–1024.
1222:2010PNAS..107.5393S
1102:2013NatNa...8..755C
915:2006PNAS..10318911S
909:(50): 18911–18916.
852:2019NanoL..19.2668S
737:2017Sci...355..950E
672:2012Sci...337.1628C
511:on a DNA computer.
233:orders of magnitude
175:In 2002: Solving a
168:In 1994: Solving a
3637:DNA nanotechnology
3167:2012-05-10 at the
3032:2010-06-18 at the
3021:2010-06-18 at the
2556:10.1039/C7RA02607B
1164:(6369): eaal2052.
982:10.1038/nmeth.3804
615:Parallel computing
600:Membrane computing
580:Computational gene
508:parallel computing
490:which generates a
488:cellular automaton
470:
381:A design called a
284:) associated with
25:
3627:Molecular biology
3527:978-0-387-73635-8
3489:978-3-540-64196-4
3465:978-3-540-65773-6
3192:(6990): 423–429.
3125:(6862): 430–434.
2940:10.1021/ja016756v
2934:(14): 3555–3561.
2898:10.1021/nl0620684
2884:(11): 2598–2603.
2597:978-3-642-10604-0
2272:(11): 1075–1081.
2150:(7714): 370–376.
2092:(7356): 368–372.
1962:(37): 4906–4911.
1848:(5272): 220–223.
1493:(5210): 583–585.
1216:(12): 5393–5398.
1038:(21): 9587–9593.
731:(6328): 950–954.
620:Quantum computing
610:Peptide computing
575:Chemical computer
496:Sierpinski gasket
462:Sierpinski gasket
251:. In particular,
213:Kevin Cherry and
199:logical functions
117:John Reif's group
96:field started by
44:molecular biology
3649:
3531:
3507:
3501:
3493:
3478:(October 1998).
3469:
3436:
3431:
3425:
3420:
3414:
3402:
3396:
3395:
3367:
3361:
3360:
3350:
3340:
3316:
3307:
3303:
3286:(9): 1165–1172.
3275:
3269:
3268:
3238:
3232:
3227:
3217:
3177:
3171:
3160:
3150:
3139:10.1038/35106533
3110:
3104:
3103:
3101:
3100:
3091:. Archived from
3082:
3043:
3037:
3012:
3006:
3005:
2995:
2985:
2961:
2955:
2951:
2919:
2913:
2909:
2873:
2867:
2863:
2838:(9): 1069–1074.
2827:
2821:
2817:
2807:
2797:
2780:(9): 4262–4266.
2765:
2759:
2754:
2710:
2701:
2700:
2658:
2649:
2643:
2642:
2640:
2608:
2602:
2601:
2575:
2569:
2568:
2558:
2526:
2520:
2519:
2485:
2463:
2457:
2456:
2438:
2414:
2408:
2407:
2382:(2): 1146–1155.
2371:
2365:
2364:
2320:
2314:
2313:
2260:
2254:
2253:
2201:
2192:
2191:
2135:
2126:
2125:
2081:
2075:
2064:
2058:
2057:
2029:
2023:
2016:
2010:
2009:
2008:, March 21, 2002
1994:
1988:
1987:
1951:
1945:
1944:
1896:
1890:
1889:
1838:"Making DNA Add"
1833:
1827:
1826:
1778:
1772:
1771:
1761:
1712:
1706:
1705:
1649:
1643:
1642:
1586:
1580:
1579:
1535:
1529:
1528:
1510:
1478:
1472:
1464:
1462:
1438:
1432:
1431:
1425:
1417:
1415:
1414:
1408:
1402:. Archived from
1401:
1389:
1387:
1363:
1357:
1356:
1350:
1342:
1340:
1339:
1333:
1327:. Archived from
1326:
1314:
1296:
1268:
1262:
1261:
1251:
1233:
1201:
1192:
1191:
1173:
1149:
1140:
1139:
1129:
1081:
1072:
1071:
1023:
1012:
1011:
1001:
961:
955:
954:
944:
926:
894:
888:
887:
846:(4): 2668–2673.
835:
829:
828:
801:10.1038/nbt.4079
779:
773:
772:
716:
710:
709:
683:
651:
630:Wetware computer
397:to some extent.
312:Toehold exchange
188:Tic-tac-toe game
170:Hamiltonian path
150:proof of concept
138:Hamiltonian path
71:proof-of-concept
3657:
3656:
3652:
3651:
3650:
3648:
3647:
3646:
3607:
3606:
3540:
3535:
3528:
3495:
3494:
3490:
3466:
3444:
3442:Further reading
3439:
3432:
3428:
3421:
3417:
3412:Wayback Machine
3403:
3399:
3368:
3364:
3317:
3310:
3276:
3272:
3239:
3235:
3178:
3174:
3169:Wayback Machine
3111:
3107:
3098:
3096:
3055:Interface Focus
3044:
3040:
3034:Wayback Machine
3023:Wayback Machine
3013:
3009:
2962:
2958:
2920:
2916:
2874:
2870:
2828:
2824:
2766:
2762:
2711:
2704:
2656:
2650:
2646:
2609:
2605:
2598:
2576:
2572:
2527:
2523:
2464:
2460:
2429:(33): 1801470.
2415:
2411:
2372:
2368:
2321:
2317:
2261:
2257:
2202:
2195:
2136:
2129:
2082:
2078:
2072:Pour la Science
2065:
2061:
2030:
2026:
2017:
2013:
1996:
1995:
1991:
1952:
1948:
1897:
1893:
1834:
1830:
1779:
1775:
1728:(7683): 72–77.
1713:
1709:
1664:(7683): 78–83.
1650:
1646:
1601:(7683): 67–71.
1587:
1583:
1536:
1532:
1479:
1475:
1439:
1435:
1419:
1418:
1412:
1410:
1406:
1399:
1397:"Archived copy"
1395:
1364:
1360:
1344:
1343:
1337:
1335:
1331:
1324:
1322:"Archived copy"
1320:
1269:
1265:
1202:
1195:
1150:
1143:
1096:(10): 755–762.
1082:
1075:
1024:
1015:
962:
958:
895:
891:
836:
832:
780:
776:
717:
713:
652:
648:
644:
639:
565:
556:
532:
504:
476:
454:
418:prostate cancer
403:
393:which can play
355:oligonucleotide
349:Catalytic DNA (
347:
326:
314:
298:
270:
241:
224:
211:
190:
162:Leonard Adleman
158:
130:Leonard Adleman
126:
94:DNA nanoscience
79:Turing machines
63:Leonard Adleman
60:
17:
12:
11:
5:
3655:
3645:
3644:
3639:
3634:
3629:
3624:
3619:
3605:
3604:
3599:
3594:
3589:
3584:
3579:
3574:
3568:
3551:
3546:
3539:
3538:External links
3536:
3534:
3533:
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3509:
3488:
3471:
3464:
3445:
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3440:
3438:
3437:
3426:
3415:
3397:
3362:
3308:
3270:
3233:
3172:
3105:
3049:(1999-12-07).
3038:
3007:
2956:
2914:
2868:
2844:10.1038/nbt862
2822:
2760:
2702:
2644:
2603:
2596:
2570:
2521:
2458:
2409:
2366:
2331:(9): 920–927.
2315:
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2127:
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2059:
2024:
2011:
1989:
1946:
1891:
1828:
1773:
1707:
1644:
1581:
1546:(2): 237–247.
1530:
1473:
1453:(2): 192–203.
1433:
1378:(1–3): 79–94.
1358:
1294:10.1.1.54.2565
1263:
1193:
1141:
1073:
1028:Strauss, Karin
1013:
976:(5): 439–442.
970:Nature Methods
956:
889:
830:
795:(3): 242–248.
774:
711:
666:(6102): 1628.
645:
643:
640:
638:
637:
632:
627:
622:
617:
612:
607:
602:
597:
595:DNA sequencing
592:
587:
582:
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564:
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555:
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531:
528:
503:
500:
472:Main article:
453:
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407:Turing machine
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3580:
3578:
3575:
3573:, Physics Web
3572:
3569:
3566:
3562:
3558:
3557:
3553:Dirk de Pol:
3552:
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3505:
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3491:
3485:
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3461:
3457:
3456:
3452:(June 2005).
3451:
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3149:
3144:
3140:
3136:
3132:
3128:
3124:
3120:
3116:
3109:
3095:on 2009-01-03
3094:
3090:
3086:
3081:
3076:
3072:
3068:
3064:
3060:
3056:
3052:
3048:
3047:Shapiro, Ehud
3042:
3035:
3031:
3028:
3024:
3020:
3017:
3011:
3003:
2999:
2994:
2989:
2984:
2979:
2975:
2971:
2967:
2960:
2954:
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2945:
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2937:
2933:
2929:
2925:
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2907:
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2899:
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2887:
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2020:DNA Computing
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2007:
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551:
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351:deoxyribozyme
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286:digital logic
283:
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28:DNA computing
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3577:Ars Technica
3555:
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3454:
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3325:PLOS Biology
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3093:the original
3058:
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3041:
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2976:(1): 57–67.
2973:
2969:
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2881:
2878:Nano Letters
2877:
2871:
2835:
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2718:
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2002:Western News
2001:
1992:
1959:
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1404:the original
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1329:the original
1276:
1272:
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1157:
1093:
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840:Nano Letters
839:
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714:
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659:
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625:Transcriptor
557:
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502:Capabilities
477:
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404:
382:
380:
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359:
348:
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271:
258:
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40:biochemistry
27:
26:
3450:Martyn Amos
3065:: 497–503.
2993:11375/23673
2623:(7): 1242.
2476:: 252–259.
570:Biocomputer
494:called the
395:tic-tac-toe
387:logic gates
194:tic-tac-toe
177:NP-complete
52:Len Adleman
34:which uses
3611:Categories
3378:(3): 5–8.
3251:(1): 3–8.
3099:2009-08-13
2483:1704.06371
1787:Biosystems
1413:2011-10-14
1338:2005-11-21
642:References
480:Wang tiles
442:protein 53
318:sticky end
98:Ned Seeman
3565:0177-6738
3498:cite book
2565:2046-2069
2508:1536-125X
2445:1613-6829
2396:1936-0851
2353:1748-3387
2310:202729100
2294:1748-3387
2234:0036-8075
2172:0028-0836
2106:0028-0836
1976:1521-3773
1925:0036-8075
1870:0036-8075
1815:0303-2647
1750:1476-4687
1702:205262182
1686:1476-4687
1623:1476-4687
1568:0022-5193
1517:0036-8075
1289:CiteSeerX
1240:0027-8424
1180:0036-8075
1118:1748-3395
1068:218504535
1052:0002-7863
990:1548-7105
933:0027-8424
868:1530-6984
825:205285821
809:1546-1696
753:0036-8075
690:0036-8075
544:DNA chips
383:stem loop
253:John Reif
215:Lulu Qian
146:test tube
115:In 2003,
110:Lila Kari
3408:Archived
3357:15583715
3265:15720184
3224:15116117
3165:Archived
3157:11719800
3089:22649583
3030:Archived
3019:Archived
3002:15112995
2948:11929243
2906:17090098
2852:12923549
2743:10073925
2697:10966324
2689:17158324
2617:Symmetry
2453:30022600
2404:29357217
2376:ACS Nano
2361:28737747
2302:31548688
2250:10053541
2242:21636773
2188:49566504
2180:29973727
2114:21776082
1984:15372637
1941:34699434
1933:11556362
1823:10963862
1768:29219968
1694:29219966
1631:29219965
1422:cite web
1347:cite web
1258:20203007
1188:29242317
1136:24077029
1060:32364723
1008:27018580
951:17142314
884:84841635
876:30896178
817:29457795
769:13470340
761:28254941
698:22903519
563:See also
520:EXPSPACE
345:DNAzymes
128:In 1994
87:in vitro
3380:Bibcode
3288:Bibcode
3215:3838955
3194:Bibcode
3148:3838952
3127:Bibcode
3080:3363030
2886:Bibcode
2814:9113977
2782:Bibcode
2751:9697423
2723:Bibcode
2715:Science
2669:Bibcode
2661:Science
2625:Bibcode
2543:Bibcode
2516:5616325
2488:Bibcode
2333:Bibcode
2274:Bibcode
2214:Bibcode
2206:Science
2152:Bibcode
2122:1735584
2042:Bibcode
1905:Science
1886:6051207
1878:8662501
1850:Bibcode
1842:Science
1795:Bibcode
1759:5786436
1730:Bibcode
1666:Bibcode
1639:4455780
1603:Bibcode
1576:6188926
1548:Bibcode
1525:7725109
1495:Bibcode
1487:Science
1311:7973651
1281:Bibcode
1273:Science
1249:2851759
1218:Bibcode
1158:Science
1127:4150546
1098:Bibcode
999:4941813
942:1748151
911:Bibcode
848:Bibcode
733:Bibcode
725:Science
668:Bibcode
660:Science
540:Caltech
492:fractal
468:, 2004.
446:in vivo
401:Enzymes
391:MAYA II
376:in vivo
371:MAYA II
339:in vivo
268:Methods
65:of the
58:History
3563:
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3486:
3462:
3435:Online
3355:
3348:534809
3345:
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3186:Nature
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3119:Nature
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1982:
1974:
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466:et al.
422:PPAP2B
367:MAYA I
134:TT-100
42:, and
3061:(4).
2856:S2CID
2805:20710
2747:S2CID
2693:S2CID
2657:(PDF)
2512:S2CID
2478:arXiv
2423:Small
2306:S2CID
2246:S2CID
2184:S2CID
2118:S2CID
1937:S2CID
1882:S2CID
1698:S2CID
1635:S2CID
1407:(PDF)
1400:(PDF)
1332:(PDF)
1325:(PDF)
1064:S2CID
880:S2CID
821:S2CID
765:S2CID
702:S2CID
426:GSTP1
181:3-SAT
3561:ISSN
3522:ISBN
3504:link
3484:ISBN
3460:ISBN
3353:PMID
3261:PMID
3220:PMID
3153:PMID
3085:PMID
3025:and
2998:PMID
2944:PMID
2902:PMID
2848:PMID
2810:PMID
2739:PMID
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864:ISSN
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694:PMID
686:ISSN
548:Perl
538:and
438:MDM2
432:and
430:PIM1
424:and
414:FokI
369:and
3632:DNA
3388:doi
3343:PMC
3333:doi
3296:doi
3284:237
3253:doi
3210:PMC
3202:doi
3190:429
3143:PMC
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3075:PMC
3067:doi
2988:hdl
2978:doi
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2800:PMC
2790:doi
2731:doi
2719:283
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