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Biological computation

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In the most literal interpretation of the term, biological computation refers to computation by means of biological systems — specifically, biological systems/processes that imbed mathematical/computational operations — hence, its application to the emerging subdiscipline of biology that explores and exploits the use of biological systems to perform mathematical/computational operations and achieve solutions to mathematical/computational problems — for example, computing with DNA molecules[1] — and that studies computational processes in biological and living systems.[2][3][4]

Parallel computing

The prospect of using molecules and chemistry to undertake massively parallel computation has been raised.[5] The notion is based upon simultaneous analysis of an assembly of molecules like DNA that are "trial" solutions and use of various chemical tricks to decide in parallel which ones fit the problem criteria. A description of one such approach is provided by Maley.[6] A practical problem has proved to be a high error rate that requires careful study.

Embedded controllers

One different kind of application for biological computation is the administration of chemotherapy. The underlying idea is that bacteria are arranged to invade a tumor to selectively produce a drug that kills the tumor. Within the injected bacteria is an embedded controller that executes the logical computation "If X is present, produce Y" or possibly, "If the rate of change of X is within certain bounds, produce Y", thereby conditionally activating the bacteria only where a tumor is present.[7]

References

  1. Kari L, Landweber LF. (2000). "Computing with DNA". Methods in Molecular Biology: Bioinformatics methods and protocols 132: pp. 413-430.
  2. Bray D. (2009). Wetware: A Computer in Every Living Cell. Yale University Press. ISBN 9780300141733.  Google Books preview.
  3. Landweber LF, Kari L. (1999). "The evolution of cellular computing: nature’s solution to a computational problem". Biosystems 52: pp. 3-13.
  4. Simeonov PL (2010). "Integral biomathics: A post-Newtonian view into the logos of bios". Progress in Biophysics and Molecular Biology: pp. 85-121. DOI:10.1016/j.pbiomolbio.2010.01.005. Research Blogging. Proof of article as published online.
  5. John H Reif (1999). "Parallel biomolecular computation: models and simulations". Algorithmica 25: pp. 142-175. DOI:10.1007/PL00008272. Research Blogging.
  6. Carlo C. Maley (1998). "DNA Computation: Theory, Practice, and Prospects". Evolutionary computation 6: pp. 201-229.
  7. JC Anderson, EJ Clarke, AP Arkin, CA Voigt (2005). "Environmentally controlled invasion of cancer cells by engineered bacteria". Journal of Molecular Biology,: pp. 619 ff. DOI:10.1016/j.jmb.2005.10.076. Research Blogging.