Signaling-pathway-based molecular computing for efficient 3-SAT problem solving

In this paper, we propose a molecular computing method based on the signaling pathways of cells. The kernel of the corresponding computing mechanism is the interaction of signaling pathways for phosphorylation- dephosphorylation regulated by kinases and phosphatases. The materials for its potential biological implementation are the signaling pathways of Rho family GTPases of in situ cells that have been simulated by us in a coarse-grained way. An instance of the 3-SAT benchmark problem is used to test the performance of signaling-pathway-based algorithms applied in NP problem solving. The theoretical result that we achieved is that both control-space complexity and time complexity is linear. In addition to this, the merits derived from the method mentioned above include scalability, robustness, programmability, controllability and autonomy. The simulation has shown that molecular computing schemes using signaling pathways are programmable for different computing units and controllable for temporal signals of pathways with ample efficiency for computing processes.

[1]  S. Kuroda,et al.  Regulation of the cytoskeleton and cell adhesion by the Rho family GTPases in mammalian cells. , 1999, Annual review of biochemistry.

[2]  Takeshi Yamada,et al.  Voice Activity Detection for Sentence Utterances Using Environment Sound Models and HMM and HMM Composition , 2001 .

[3]  Mitsunori Ogihara,et al.  Molecular computation: DNA computing on a chip , 2000, Nature.

[4]  Leonard M. Adleman,et al.  Solution of a Satisfiability Problem on a Gel-Based DNA Computer , 2000, DNA Computing.

[5]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[6]  T Pawson,et al.  Cell communication: the inside story. , 2000, Scientific American.

[7]  Shi V. Liu.  Debating controversies can enhance creativity , 2000, Nature.

[8]  Robin Milner,et al.  Bigraphical reactive systems: basic theory , 2001 .

[9]  Toshinobu Harada,et al.  Development of Shape Design System Using Curves with Designer's Intention , 2001 .

[10]  Mitsunori Ogihara,et al.  A DNA-Based Random Walk Method for Solving k-SAT , 2000, DNA Computing.

[11]  K Sakamoto,et al.  Molecular computation by DNA hairpin formation. , 2000, Science.

[12]  L M Adleman,et al.  Molecular computation of solutions to combinatorial problems. , 1994, Science.

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

[14]  R. Mollica,et al.  Waging a new kind of war. Invisible wounds. , 2000, Scientific American.

[15]  Bruno Courcelle,et al.  The Expression of Graph Properties and Graph Transformations in Monadic Second-Order Logic , 1997, Handbook of Graph Grammars.

[16]  U. Schöning.  A probabilistic algorithm for k-SAT and constraint satisfaction problems , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[17]  R. Milner,et al.  Bigraphical Reactive Systems , 2001, CONCUR.

[18]  Lloyd M. Smith,et al.  DNA computing on surfaces , 2000, Nature.