With so many different methods and models emerging from the current research, DNA computing can be more accurately described as a collection of new computing paradigms rather than a single focus. Each of these different paradigms within biomolecular computing can be associated with different potential applications that may prove to place them at an advantage over conventional methods. Many of these models share certain features that lend them to categorization by these potential advantages. However, there exist enough similarities and congruencies that hybrid models will be possible, and that advances made in both ―classic‖ and ―natural‖ areas of DNA computing will be mutually beneficial to both areas of research. Advancements in DNA computing may also serve to enhance understanding of both the natural and computer sciences. For these reasons, and due to the many areas dependent on each of computer science, mathematics, natural science, and engineering, continued interdisciplinary collaboration is very important to any future progress in all areas of this new field.
A ―killer app‖ is yet to be found for DNA computation, but might exist outside the bulk of current research, in the domain of DNA2DNA applications and other more natural models and applications of manipulated DNA. This direction is particularly interesting because it is an area in which DNA based solutions are not only an improvement over existing techniques, but may prove to be the only feasible way of directly solving such problems that involve the direct interaction with biological matter.
On the ―classical‖ front, problem specific computers may prove to be the first practical use of DNA computation for several reasons. First, a problem specific computer will be easier to design and implement, with less need for functional complexity and flexibility. Secondly, DNA computing may prove to be entirely inefficient for a wide range of problems, and directing efforts on universal models may be diverting energy away from its true calling. Thirdly, the types of hard computational problems that DNA based computers may be able to effectively solve are of sufficient economic importance that a dedicated processor would be financially reasonable. As well, these problems will be likely to require extensive time they would preclude the need for a more versatile and interactive system that may be able to be implemented with a universal computing machine.
Even if the current difficulties found in translating theoretical DNA computing models into real life are never sufficiently overcome, there is still potential for other areas of development. Future applications might make use of the error rates and instability of DNA based computation methods as a means of simulating and predicting the emergent behavior of complex systems. This could pertain
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to weather forecasting, economics, and lead to more a scientific analysis of- social science and the humanities. Such a system might rely on inducing increased error rates and mutation through exposure to radiation and deliberately inefficient encoding schemes. Similarly, methods of DNA computing might serve as the most obvious medium for use of evolutionary programming for applications in design or expert systems. DNA computing might also serve as a medium to implement a true fuzzy logic system.
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17.
LIMITATIONS
:However, there are certain shortcomings to the development of the DNA computers:
A factor that places limits on his method is the error rate for each operation. Since these operations are not deterministic but stochastically driven, each step contains statistical errors, limiting the number of iterations one can do successively before the probability of producing an error becomes greater than producing the correct result.
Algorithms proposed so far use relatively slow molecular-biological operations.
Each primitive operation takes hours when you run them with a small test tube of DNA. Some concrete algorithms are just for solving some concrete problems. Every Generating solution sets, even for some relatively simple problems, may require impractically large amounts of memory. Also, with each DNA molecule acting as a separate processor, there are problems with transmitting information from one molecule to another that have yet to be solved.
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18.
Conclusion
:DNA computers will become more common for solving very complex problems; Just as DNA cloning and sequencing were once manual tasks, DNA computers will also become automatedes. Studying DNA computers may also lead us to a better future enhancement.
With so many possible advantages over conventional techniques, DNA computing has great potential for practical use. Future work in this field should begin to incorporate cost-benefit analysis so that comparisons can be more appropriately made with existing techniques and so that increased funding can be obtained for this research that has the potential to benefit many circles of science and Industry.
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19. REFERENCES :
1. IEEE papers on DNA computing
2. COMPUTING WITH DNA,Leonard M.Adleman,Scientific American, August 1998.
3. Molecular Computation of Solutions to Combinatorial Problems‖, L.M. Adleman, Science Vol. 266 pp1021-1024, 11 Nov 1994.
4. ―Introduction to computational molecular biology‖ by Joao Setubal and Joao Meidans -Sections 9.1 and 9.3
5. ―DNA computing, new computing paradigms‖ by G.Paun, G.Rozenberg, A.Salomaa-chapter 2
6. ―Self-Assembled DNA Scaffolding‖ Science Daily, August 20 2009.
DNA computing (web)
1. Kershner et al. Placement and orientation of individual DNA shapes on lithographically patterned surfaces. Nature Nanotechnology, 2009; DOI: 10.1038/nnano.2009.220