Ligation module for in vitro selection in DNA computing

In this paper a classical AI problem is proposed to be solved by DNA computing: theorem proving. Since the complexity grows exponentially with the size of the problem, the solving process should be done in parallel. Massive parallelism is one of the advantages of DNA computers. It will be shown that the resolution refutation proof can be readily implemented by DNA hybridisation and ligation. Microreactors lend themselves to a relatively simple implementation of DNA computing. Not only is the design of the DNA critical for the success of the system but also the architecture of the microfluidic structure. Here the DNA performs the computation, while the microfluidics aids the biochemical steps necessary to manipulate the DNA, i.e. hybridisation and ligation.

[1]  John S. McCaskill,et al.  DNA computing in microreactors , 2001, SPIE Micro + Nano Materials, Devices, and Applications.

[2]  S. Quake,et al.  Monolithic microfabricated valves and pumps by multilayer soft lithography. , 2000, Science.

[3]  Melvin Fitting,et al.  First-Order Logic and Automated Theorem Proving , 1990, Graduate Texts in Computer Science.

[4]  M. Sahani,et al.  Algorithmic Self-Assembly of DNA , 2006 .

[5]  Piotr Wasiewicz,et al.  The Inference Based on Molecular Computing , 2000, Cybern. Syst..

[6]  Byoung-Tak Zhang,et al.  PDMS valves in DNA computers , 2005, SPIE Micro + Nano Materials, Devices, and Applications.

[7]  John S. McCaskill,et al.  Hybrid poly(dimethylsiloxane)-silicon microreactors used for molecular computing , 2002 .

[8]  Christian B. Suttner.  SPTHEO - A Parallel Theorem Prover , 2004, Journal of Automated Reasoning.

[9]  R J Lipton,et al.  DNA solution of hard computational problems. , 1995, Science.

[10]  L F Landweber,et al.  Molecular computation: RNA solutions to chess problems , 2000, Proc. Natl. Acad. Sci. USA.

[11]  J S McCaskill.  Optically programming DNA computing in microflow reactors. , 2001, Bio Systems.

[12]  Clifford R. Johnson,et al.  Solution of a 20-Variable 3-SAT Problem on a DNA Computer , 2002, Science.

[13]  Masami Hagiya,et al.  Towards parallel evaluation and learning of Boolean μ-formulas with molecules , 1997, DNA Based Computers.

[14]  Satoshi Kobayashi,et al.  Horn Clause Computation with DNA Molecules , 1999, J. Comb. Optim..

[15]  E. Winfree.  Algorithmic Self-Assembly of DNA: Theoretical Motivations and 2D Assembly Experiments , 2000, Journal of biomolecular structure & dynamics.

[16]  V. Mihalache.  Prolog approach to DNA computing , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[17]  Byoung-Tak Zhang,et al.  DNA Implementation of Theorem Proving with Resolution Refutation in Propositional Logic , 2002, DNA.

[18]  Danny van Noort,et al.  A Programmable Molecular Computer in Microreactors , 2004, DNA.

[19]  Satoshi Kobayashi,et al.  Horn Clause Computation by Self-assembly of DNA Molecules , 2001, DNA.