DNA computing

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For hypothetical computers using brain-to-brain interfaces see Biological computer

DNA computing is a form of computing which uses DNA, biochemistry and molecular biology, instead of the traditional silicon-based computer technologies. DNA computing, or, more generally, biomolecular computing, is a fast developing interdisciplinary area. Research and development in this area concerns theory, experiments, and applications of DNA computing. The term "molectronics" has sometimes been used, but this term had already been used for an earlier technology, a then-unsuccessful rival of the first integrated circuits;^[1] this term has also been used more generally, for molecular-scale technology.^[2]

Contents

• 1 History
• 2 Capabilities
• 3 Methods
  • 3.1 DNAzymes
  • 3.2 Enzymes
  • 3.3 Toehold exchange
  • 3.4 Algorithmic self-assembly
• 4 See also
• 5 References
• 6 Further reading
• 7 External links

History

This field was initially developed by Leonard Adleman of the University of Southern California, in 1994.^[3] Adleman demonstrated a proof-of-concept use of DNA as a form of computation which solved the seven-point Hamiltonian path problem. Since the initial Adleman experiments, advances have been made and various Turing machines have been proven to be constructible.^[4][5]
While the initial interest was in using this novel approach to tackle NP-hard problems, it was soon realized that they may not be best suited for this type of computation, and several proposals have been made to find a "killer application" for this approach. In 1997, computer scientist Mitsunori Ogihara working with biologist Animesh Ray suggested one to be the evaluation of Boolean circuits and described an implementation.^[6][7]
In 2002, researchers from the Weizmann Institute of Science in Rehovot, Israel, unveiled a programmable molecular computing machine composed of enzymes and DNA molecules instead of silicon microchips.^[8] On April 28, 2004, Ehud Shapiro, Yaakov Benenson, Binyamin Gil, Uri Ben-Dor, and Rivka Adar at the Weizmann Institute announced in the journal Nature that they had constructed a DNA computer coupled with an input and output module which would theoretically be capable of diagnosing cancerous activity within a cell, and releasing an anti-cancer drug upon diagnosis.^[9]
In January 2013, researchers were able to store a JPEG photograph, a set of Shakespearean sonnets, and an audio file of Martin Luther King, Jr.'s speech I Have a Dream on DNA digital data storage.^[10]
In March 2013, researchers created a transcriptor (a biological transistor).

Capabilities

DNA computing is fundamentally similar to parallel computing in that it takes advantage of the many different molecules of DNA to try many different possibilities at once.^[11] 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 on a DNA computer. As an example, Aran Nayebi^[12] has provided a general implementation of Strassen's matrix multiplication algorithm on a DNA computer, although there are problems with scaling. In addition, Caltech researchers have created a circuit made from 130 unique DNA strands, which is able to calculate the square root of numbers up to 15.^[13]
DNA computing does not provide any new capabilities from the standpoint of computability theory, 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 (EXPSPACE problems) on von Neumann machines, 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.