Quorum sensing P systems

This paper continues the investigation of population P systems model [F. Bernardini, M. Gheorghe, Population P systems, Journal of Universal Computer Science 10 (5) (2004) 509-539] by considering bacterium quorum sensing (QS) phenomena as the basis of the new approach. A new computational model called QS P system is introduced. It is proved that QS P systems are able to simulate counter machines, and hence they are equivalent in power to Turing machines. An example of a QS P system modelling the behaviour of Vibrio fischeri bacteria colonies is also presented and the emergence of the QS mechanism is illustrated.

[1]  Mario J Pérez-Jiménez,et al.  Membrane computing: brief introduction, recent results and applications. , 2006, Bio Systems.

[2]  G. Yarrington.  Molecular Cell Biology , 1987, The Yale Journal of Biology and Medicine.

[3]  Rudolf Freund,et al.  P colonies working in the maximally parallel and in the sequential mode , 2005, Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05).

[4]  R. Paton,et al.  Intracellular signalling proteins as smart' agents in parallel distributed processes. , 1999, Bio Systems.

[5]  Grzegorz Rozenberg,et al.  Handbook of formal languages, vol. 3: beyond words , 1997 .

[6]  K. Winzer,et al.  Bacterial cell-to-cell communication: sorry, can't talk now - gone to lunch! , 2002, Current opinion in microbiology.

[7]  Florent Jacquemard,et al.  An Analysis of a Public Key Protocol with Membranes , 2005 .

[8]  Ion Petre,et al.  Self-aware Computing Systems , 2016, Natural Computing Series.

[9]  Gabriel Ciobanu,et al.  Applications of Membrane Computing , 2006, Applications of Membrane Computing.

[10]  Marian Gheorghe,et al.  An Environment Aware P-System Model of Quorum Sensing , 2005, CiE.

[11]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[12]  Mike Holcombe,et al.  Coupled computational simulation and empirical research into the foraging system of Pharaoh's ant (Monomorium pharaonis). , 2004, Bio Systems.

[13]  Mario de Jesús Pérez Jiménez,et al.  Modelling Vibrio fischeri’s behaviour Using P Systems , 2005 .

[14]  Hiroshi Matsuno,et al.  Boundary Formation by Notch Signaling in Drosophila Multicellular Systems: Experimental Observations and Gene Network Modeling by Genomic Object Net , 2002, Pacific Symposium on Biocomputing.

[15]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[16]  Luca Cardelli,et al.  BioAmbients: an abstraction for biological compartments , 2004, Theor. Comput. Sci..

[17]  H. Arnstein.  The molecular biology of the cell : B. Alberts, D. Bray, J. Lewis, M. Raff, K. Roberts and J.D. Watson Garland Publishing; New York, London, 1983 xxxix + 1181 pages. $33.95 (hardback); $27.00, £14.95 (paperback, only in Europe) , 1986 .

[18]  B. Alberts,et al.  Molecular Biology of the Cell 4th edition , 2007 .

[19]  Benedikt Löwe,et al.  New Computational Paradigms , 2005 .

[20]  Vincenzo Manca,et al.  P Systems with Boundary Rules , 2002, WMC-CdeA.

[21]  Akif Uzman,et al.  Molecular Cell Biology (4th edition): Harvey Lodish, Arnold Berk, S. Lawrence Zipursky, Paul Matsudaira, David Baltimore and James Darnell; Freeman & Co., New York, NY, 2000, 1084 pp., list price $102.25, ISBN 0-7167-3136-3 , 2001 .

[22]  Marian Gheorghe,et al.  Population P Systems , 2004, J. Univers. Comput. Sci..

[23]  M. Holcombe,et al.  The epitheliome: agent-based modelling of the social behaviour of cells. , 2004, Bio Systems.

[24]  Hendrik Jan Hoogeboom,et al.  Simulating Counter Automata by P Systems with Symport/Antiport , 2002, WMC-CdeA.

[25]  Gheorghe Paun,et al.  Membrane Computing , 2002, Natural Computing Series.

[26]  Gheorghe Paun,et al.  Grammar Systems , 1997, Handbook of Formal Languages.

[27]  Gabriel Ciobanu,et al.  Structural Operational Semantics of P Systems , 2005, Workshop on Membrane Computing.

[28]  Marian Gheorghe,et al.  An Agent-Based Behavioural Model of Monomorium Pharaonis Colonies , 2003, Workshop on Membrane Computing.

[29]  Erzsébet Csuhaj-Varjú,et al.  Eco-grammar systems: a grammatical framework for studying lifelike interactions , 1997 .

[30]  David I. Lewin,et al.  DNA computing , 2002, Comput. Sci. Eng..

[31]  Gheorghe Paun,et al.  DNA Computing: New Computing Paradigms , 1998 .

[32]  J. Davies,et al.  Molecular Biology of the Cell , 1983, Bristol Medico-Chirurgical Journal.

[33]  Zbigniew Michalewicz,et al.  Handbook of Evolutionary Computation , 1997 .

[34]  Maurice Margenstern,et al.  On P systems with bounded parallelism , 2005, Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05).

[35]  S. Kjelleberg,et al.  Luminescence control in the marine bacterium Vibrio fischeri: An analysis of the dynamics of lux regulation. , 2000, Journal of molecular biology.

[36]  David Harel,et al.  The immune system as a reactive system: modeling T cell activation with statecharts , 2001, Proceedings IEEE Symposia on Human-Centric Computing Languages and Environments (Cat. No.01TH8587).

[37]  A. Lindenmayer.  Mathematical models for cellular interactions in development. II. Simple and branching filaments with two-sided inputs. , 1968, Journal of theoretical biology.

[38]  Gheorghe Paun,et al.  Applications of Membrane Computing (Natural Computing Series) , 2005 .

[39]  Gheorghe Paun,et al.  Grammar Systems: A Grammatical Approach to Distribution and Cooperation , 1995, ICALP.

[40]  A. Lindenmayer.  Mathematical models for cellular interactions in development. I. Filaments with one-sided inputs. , 1968, Journal of theoretical biology.

[41]  Jeffrey Horn,et al.  Handbook of evolutionary computation , 1997 .

[42]  D. Searls,et al.  Robots in invertebrate neuroscience , 2002, Nature.