DNA computing
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DNA computing is a form of computing which uses DNA and biochemistry and molecular biology, instead of the traditional silicon-based computer technologies.
This field was initially developed by Leonard Adleman of the University of Southern California. In 1994, Adleman demonstrated a proof-of-concept use of DNA as a form of computation which was used to solve the seven-point Hamiltonian path problem. Since the initial Adleman experiments, advances have been made and various Turing machines have been proven to be constructable.
There are works over one dimensional lengths, bidimensional tiles, and even three dimensional DNA graphs processing.
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. This was coupled with an input and output module and is capable of diagnosing cancerous activity within a cell, and then releasing an anti-cancer drug upon diagnosis.
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.
For certain specialized problems, DNA computers are faster and smaller than any other computer built so far. But DNA computing does not provide any new capabilities from the standpoint of computational complexity theory, the study of which computational problems are difficult to solve. For example, problems which grow exponentially with the size of the problem (EXPSPACE problems) on von Neumann machines still grow 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. (Quantum computing, on the other hand, does provide some interesting new capabilities).
DNA computing overlaps with, but is distinct from, DNA nanotechnology. The latter uses the specificity of Watson-Crick basepairing to make novel structures out of DNA. These structures can be used for DNA computing, but they do not have to be. Additionally, DNA computing can be done without using the types of molecules made possible by DNA Nanotechnology (as the above examples show).
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[edit] Examples of DNA computing
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- Leonard M. Adleman (1994-11-11). "Molecular Computation Of Solutions To Combinatorial Problems". Science (journal) 266 (11): 1021–1024. — The first DNA computing paper. Describes a solution for the directed Hamiltonian path problem.
- Martyn Amos (June 2005). Theoretical and Experimental DNA Computation. Springer. ISBN 3-540-65773-8. — The first general text to cover the whole field.
- Dan Boneh, Christopher Dunworth, Richard J. Lipton, and Jiri Sgall (1996). "On the Computational Power of DNA". DAMATH: Discrete Applied Mathematics and Combinatorial Operations Research and Computer Science 71. — Describes a solution for the boolean satisfiability problem.
- Gheorge Paun, Grzegorz Rozenberg, Arto Salomaa (October 1998). DNA Computing - New Computing Paradigms. Springer-Verlag. ISBN 3-540-64196-3. — 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.
- Lila Kari, Greg Gloor, Sheng Yu (January 2000). "Using DNA to solve the Bounded Post Correspondence Problem". Theoretical Computer Science 231 (2): 192–203. — Describes a solution for the bounded Post correspondence problem, a hard-on-average NP-complete problem.
- The history of the International Meeting on DNA Computing (Proceedings - Links) -- [1]
