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Abstract
Introduction
Questions
Resulting Challenges
References

Topics in Membrane Computing : After CMC 12 , Before BWMC 10

Profile image of Marian GheorgheMarian Gheorghe

2011

Abstract

What follows is a list of open problems and research topics compiled by the two editors of this “mega-paper”, with the authors who contributed to this list mentioned together with their problems and research topics. The idea of such a collection occurred during CMC 2011, held in Fontainebleau, Paris, France (23 26 August 2011), and the result is meant to be a working material for the Tenth Brainstorming Week on Membrane Computing, Sevilla, Spain (January 30 February 3, 2012).

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References (186)

  1. A. Alhazov: Minimal Parallelism and Number of Membrane Polarizations. The Com- puter Science Journal of Moldova, 18, 2(53), 2010, 149-170. http://www.math.md/publications/csjm/issues/v18-n2/10284/
  2. A. Alhazov: Minimal Parallelism and Number of Membrane Polarizations. In: H.J. Hoogeboom, Gh. Pȃun, G. Rozenberg, eds.: Preproceedings of the Seventh Interna- tional Workshop on Membrane Computing, WMC7, Lorentz Center, Leiden, 2006, 74-87. http://wmc7.liacs.nl/proceedings/WMC7Alhazov.pdf
  3. A. Alhazov: Properties of Membrane Systems. In: M. Gheorghe, Gh. Pȃun, S. Ver- lan, eds.: -it Preproceedings of the Twelfth International Conference on Membrane Computing, CMC12, Fontainebleau, 2011, 3-14. http://cmc12.lacl.fr/cmc12proceedings.pdf
  4. A. Alhazov, C. Ciubotaru, S. Ivanov, Yu. Rogozhin: The Family of Languages Gen- erated by Non-cooperative Membrane Systems. Membrane Computing. 11th Inter- national Conference, CMC 2010, Jena, 2010. Revised Selected Papers (M. Gheorghe, Th. Hinze, Gh. Pȃun, G. Rozenberg, A. Salomaa, eds.) LNCS 6501, Springer, 2011, 65-80. http://www.springerlink.com/content/gt07j477k20204l7/
  5. A. Alhazov, C. Ciubotaru, S. Ivanov, Yu. Rogozhin: Membrane Systems Languages Are Polynomial-Time Parsable. The Computer Science Journal of Moldova, 18, 2(53), 2010, 139-148. http://www.math.md/publications/csjm/issues/v18-n2/10282/
  6. A. Alhazov, R. Freund, Yu. Rogozhin: Computational Power of Symport/Antiport: History, Advances and Open Problems. In: R. Freund, Gh. Pȃun, G. Rozenberg, A. Salomaa, eds.: Membrane Computing, 6th International Workshop, WMC 2005, Vienna, Revised Selected and Invited Papers, LNCS 3850, Springer, 2006, 1-30. http://springerlink.metapress.com/index/f500782x34331741
  7. A. Alhazov, S. Ivanov, Yu. Rogozhin: Polymorphic P Systems. In: M. Gheorghe, T. Hinze, Gh. Pȃun, G. Rozenberg, A. Salomaa, eds., 11th International Conference on Membrane Computing, CMC 2010. LNCS 6501, pp. 81 -94. Springer, Berlin (2010). References
  8. L. Cienciala, L. Ciencialová: Eco-P colonies. In Pȃun et al., eds, WMC 2009, LNCS 5957, Springer, 201-209.
  9. L. Ciencala, L. Ciencialová, E. Csuhaj-Varj, Gy. Vaszil, PCol Automata: Recognizing strings with P colonies. In: Proc. BWMC 2010, Sevilla, 2010, M.A. Martnez-del-Amor et al., eds., Fénix Editora, Sevilla, 2010, 65-76.
  10. E. Csuhaj-Varj, Gy. Vaszil: A Connection Between Finite dP Automata and Multi- head Finite Automata. In Proc. Twelfth International Conference on Membrane Computing, Fontainebleau, 23-26 August, 2011. M. Gheorghe, Gh. Pȃun, S. Verlan, eds., University of Paris Est, Crteil Val de Marne, 2011, 109-126.
  11. R. Freund, M. Kogler, G. Pȃun, M.J. Pérez-Jiménez: On the power of P and dP au- tomata. Annals of Bucharest University. Mathematics-Informatics Series, 63, 2009, 5-22.
  12. M. Kutrib, Nature-Based Problems in Cellular Automata, CiE 2011, LNCS 6735, Springer, 2011, 171-180.
  13. M. Kutrib, J. Lefevre, A. Malcher: The Size of One-Way Cellular Automata. Au- tomata 2010: Discrete Mathematics and Theoretical Computer Science Proceedings, DMTCS, 2010, 71-90.
  14. M. Holzer, M. Kutrib: Cellular Automata and the Quest for Nontrivial Artificial Self-Reproduction. Int. Conf. on Membrane Computing, CMC 2010, LNCS 6501, Springer, 2010, 19-36.
  15. G. Pȃun, G. Rozenberg, A. Salomaa, eds.: The Oxford Handbook of Membrane Com- puting, Oxford University Press, 2010.
  16. G. Pȃun, M.J. Pérez-Jiménez, Solving Problems in a Distributed Way in Membrane Computing: dP Systems, International Journal of Computers, Communication & Control, V(2), 2010, 238-250.
  17. G. Pȃun, M.J. Pérez-Jiménez: P and dP automata: A survey. In: C.S. Calude, G. Rozenberg, A. Salomaa, eds., Rainbow of Computer Science, LNCS, 6570, pages 102-115, Springer, Berlin, 2011.
  18. G. Pȃun, M.J. Pérez-Jiménez, An Infinite Hierarchy of Languages Defined by dP Systems. Submitted, 2010.
  19. E. Csuhaj-Varjú, M. Oswald, Gy. Vaszil: P automata. In: Gh. Pȃun, G. Rozenberg, A. Salomaa, eds., The Oxford Handbook of Membrane Computing, chapter 6, pages 144-167. Oxford University Press, 2010.
  20. E. Csuhaj-Varjú, Gy. Vaszil: P automata or purely communicating accepting P sys- tems. In: Gh. Pȃun, G. Rozenberg, A. Salomaa, C. Zandron, eds., Membrane Comput- ing, International Workshop, WMC-CdeA, Curtea de Arges, Romania, August 19-23, 2002, Revised Papers, LNCS 2597, pages 219-233. Springer, Berlin, 2003.
  21. R. Freund, M. Kogler, Gh. Pȃun, M.J. Pérez-Jiménez: On the power of P and dP au- tomata. Annals of Bucharest University Mathematical-Informatics Series, LVIII:5-22, 2009.
  22. J.E. Hopcroft, J.D. Ullman: Introduction to Automata Theory, Languages, and Com- putation. Addison-Wesley, Reading, MA, 1979.
  23. Gh. Pȃun, M.J. Pérez-Jiménez: Solving problems in a distributed way in membrane computing: dP systems. International Journal of Computing, Communication and Control, V(2):238-250, 2010.
  24. Gh. Pȃun, M.J. Pérez-Jiménez: P and dP automata: A survey. In: C. Calude, G. Rozenberg, A. Salomaa, eds., Rainbow of Computer Science, LNCS 6570, pages 102-115. Springer, Berlin, 2011.
  25. Gh. Pȃun, M.J. Pérez-Jiménez: An infinite hierarchy of languages defined by dP sys- tems. Theoretical Computer Science, to appear.
  26. Gy. Vaszil: On the parallelizability of languages accepted by P automata. In J. Kele- men and A. Kelemenová, editors, Computation, Cooperation, and Life. Essays Ded- icated to Gheorghe Pȃun on the Occasion of His 60th Birthday, LNCS 6610, pages 170-178. Springer, Berlin Heidelberg, 2011.
  27. A. Alhazov, R. Freund, A. Leporati, M. Oswald, C. Zandron: (Tissue) P systems with unit rules and energy assigned to membranes. Fundamenta Informaticae, 74:391-408, 2006.
  28. J.T. Gill: Computational complexity of probabilistic Turing machines. In Proceedings of the Sixth Annual ACM Symposium on Theory of Computing, STOC '74, pages 91- 95, 1974.
  29. A. Leporati, D. Besozzi, P. Cazzaniga, D. Pescini, C. Ferretti: Computing with energy and chemical reactions. Natural Computing, 9:493-512, 2010.
  30. A. Leporati, C. Zandron, G. Mauri: Simulating the Fredkin gate with energy-based P systems. Journal of Universal Computer Science, 10(5):600-619, 2004.
  31. Alberto Leporati, Claudio Zandron, Giancarlo Mauri. Reversible P systems to sim- ulate Fredkin circuits. Fundamenta Informaticae, 74:529-548, 2006.
  32. N. Murphy, D. Woods: The computational power of membrane systems under tight uniformity conditions. Natural Computing, 10(1):613-632, 2011.
  33. M.J. Pérez-Jiménez: A computational complexity theory in membrane computing. In Gh. Pȃun, M.J. Pérez-Jiménez, A. Riscos-Núñez, G. Rozenberg, A. Salomaa, eds., Membrane Computing, 10th International Workshop, WMC 2009, LNCS 5957, 125- 148. Springer, 2010.
  34. M.J. Pérez-Jiménez, Á. Romero-Jiménez, F. Sancho-Caparrini: Complexity classes in models of cellular computing with membranes. Natural Computing, 2(3):265-284, 2003.
  35. A.E. Porreca, A. Leporati, G. Mauri, C. Zandron: Introducing a space complexity measure for P systems. International Journal of Computers, Communications & Control, 4(3):301-310, 2009.
  36. A.E. Porreca, A. Leporati, G. Mauri, C. Zandron: P systems simulating oracle com- putations. In M. Gheorghe, Gh. Pȃun, S. Verlan, eds., Pre-Proceedings of the Twelfth International Conference on Membrane Computing 2011 (CMC12), pages 433-445, 2011.
  37. A.E. Porreca, A. Leporati, G. Mauri, C. Zandron: P systems with active membranes working in polynomial space. International Journal of Foundations of Computer Science, 22(1):65-73, 2011.
  38. Gh. Pȃun: P systems with active membranes: Attacking NP-complete problems. Journal of Automata, Languages and Combinatorics, 6(1):75-90, 2001.
  39. P. Sosík, A. Rodríguez-Patón: Membrane computing and complexity theory: A char- acterization of PSPACE. Journal of Computer and System Sciences, 73(1):137-152, 2007.
  40. S. Toda: PP is as hard as the polynomial-time hierarchy. SIAM Journal on Com- puting, 20(5):865-877, 1991.
  41. A. Alhazov, M.J. Pérez-Jiménez: Uniform Solution to QSAT Using Polarizationless Active Membranes. In Machines, Computations and Universality (MCU), J. Durand- Lose and M. Margenstern, eds., LNCS 4664, Springer, 2007, 122-133.
  42. R. Greenlaw, H. James Hoover, W.L. Ruzzo: Limits to parallel computation:P- completeness Theory. Oxford University Press, 1995.
  43. M.A. Gutiérrez-Naranjo, M.J. Pérez-Jiménez, A. Riscos-Núñez, F.J. Romero- Campero: Computational Efficiency of Dissolution Rules in Membrane Systems. In- ternational Journal of Computer Mathematics, 83 (2006), 593-611.
  44. N. Murphy, D. Woods: The Computational Power of Membrane Systems Under Tight Uniformity Conditions. Natural Computing, 10 (2011), 613-??.
  45. N. Murphy, D. Woods: Active Membrane Systems Without Charges and Using Only Symmetric Elementary Division Characterise P.In Membrane Computing, 8th Inter- national Workshop, WMC 2007, LNCS 4869, Springer, 2007, 367-384.
  46. C.H. Papadimitriou: Computational Complexity. Addison Wesley, 1993.
  47. Gh. Pȃun: Further Twenty Six Open Problems in Membrane Computing. In Pro- ceedings of the Third Brainstorming Week on Membrane Computing, Sevilla (Spain), 2005, 249-262.
  48. D. Woods, N. Murphy, M.J. Pérez-Jiménez, A. Riscos-Núñez: Membrane Dissolution and Division in P. In Unconventional Computation, 5715 (2009), 262-276.
  49. Gh. Pȃun: P Systems with Active Membranes: Attacking NP Complete Problems. CDMTCS Technical Report 102-1999.
  50. M. Cavaliere, V. Deufemia: Further Results on Time-Free P Systems. Int. Journal of Foundations of Computer Science, 17,1, 2006, pp. 69 -89.
  51. M. Cavaliere, D. Sburlan: Time-Independent P Systems. Membrane Computing. Int. Workshop WMC 2004, Milan, Italy, 2004 (G. Mauri, Gh. Pȃun, M.J. Pérez-Jiménez, G. Rozenberg, A. Salomaa, Eds.), LNCS 3365, Springer, 2005, pp. 239 -258.
  52. M.A. Gutiérrez-Naranjo, M.J. Pérez-Jiménez, A. Riscos-Núñez, F.J. Romero- Campero: Computational Efficiency of Dissolution Rules in Membrane Systems. Int. J. Computer Mathematics, 83 (2006), 593-611.
  53. 9 Numerical P Systems Cristian Vasile 1 , Ana Brânduşa Pavel 1 , Ioan Dumitrache 1 , Gheorghe Pȃun 2 References
  54. O. Arsene, C. Buiu, N. Popescu: SNUPS -A simulator for numerical membrane computing. Intern. J. of Innovative Computing, Information and Control, 7, 6 (2011), 3509-3522.
  55. C. Buiu, O. Arsene, C. Cipu, M. Pȃtraşcu: A software tool for modeling and simula- tion of numerical P systems. BioSystems, 103, 3 (2011), 442-447.
  56. C. Buiu, C. Vasile, O. Arsene: Development of membrane controllers for mobile robots. Information Science, accepted.
  57. M. Minsky: Computation: Finite and Infinite Machines. Prentice-Hall, 1967.
  58. A.B. Pavel: Membrane controllers for cognitive robots. Master Thesis, Department of Automatic Control and System Engineering, Politehnica University of Bucharest, Febr. 2011.
  59. A.B. Pavel, O. Arsene, C. Buiu: Enzymatic numerical P systems -a new class of membrane computing systems. The IEEE Fifth Intern. Conf. on Bio-Inspired Com- puting. Theory and applications. BIC-TA 2010, Liverpool, Sept. 2010, 1331-1336.
  60. A.B. Pavel, C. Buiu: Using enzymatic numerical P systems for modeling mobile robot controllers. Natural Computing, doi: 10.1007/s11047-011-9286-5, in press.
  61. A.B. Pavel, C. Vasile, C. Buiu: Robot controllers implemented with enzymatic nu- merical P systems. submitted.
  62. Gh. Pȃun, R. Pȃun: Membrane computing and economics: Numerical P systems. Fundamenta Informaticae, 73 (2006), 213-227.
  63. Gh. Pȃun, G. Rozenberg, A. Salomaa, eds.: The Oxford Handbook of Membrane Computing. Oxford Univ. Press, 2010.
  64. The P Systems Web Page: http://ppage.psystems.eu.
  65. C. Vasile, A.B. Pavel, I. Dumitrache, Gh. Pȃun: On the power of enzymatic numerical P systems. Submitted, 2011.
  66. O. Andrei, G. Ciobanu, D. Lucanu: A Rewriting Logic Framework for Operational Semantics of Membrane Systems. Theoretical Computer Science, 373, 2007, 163-181.
  67. F. Bernardini, M. Gheorghe, F.J. Romero-Campero, N. Walkinshaw: A Hybrid Ap- proach to Modelling Biological Systems. Int. Conf. on Membrane Computing, CMC 2007, LNCS 4860, Springer, 2007, 138-159.
  68. M. Gheorghe, F. Ipate, C. Dragomir: Formal Verification and Testing based on P Systems. Int. Workshop on Membrane Computing, WMC 2009, LNCS 5957, Springer, 2009, 54-65.
  69. F. Ipate, A. T ¸urcanu: Modelling, verification and testing of P systems using Rodin and ProB. Ninth Brainstorming Week on Membrane Computing, 2011, 209-220
  70. F. Ipate, M. Gheorghe, R. Lefticaru: Test generation from P systems using model checking. Journal of Logic and Algebraic Programming, 79(6), 2010, 350-362
  71. F. Ipate, R. Lefticaru, C. Tudose: Formal verification of P systems using Spin. Inter- national Journal of Foundations of Computer Science, 22(1), 2011, 133-142
  72. F. Ipate, R. Lefticaru, I. Pérez-Hurtado, M.J. Pérez-Jiménez, C. Tudose: Formal Verifi- cation of P Systems with Active Membranes through Model Checking. Int. Conference on Membrane Computing, CMC12, 2011, 241-252.
  73. O. Agrigoroaiei, G. Ciobanu: Reversing Computation in Membrane Systems. Journal of Logic and Algebraic Programing, vol. 79(3-5), 278-288, 2010.
  74. O. Agrigoroaiei, G. Ciobanu: Rule-based and Object-based Event Structures for Membrane Systems. Journal of Logic and Algebraic Programing, vol. 79(6), 295-303, 2010.
  75. O. Agrigoroaiei, G. Ciobanu: Quantitative Causality in Membrane Systems. Pro- ceedings of the Twelfth International Conference on Membrane Computing, 53-63, 2011.
  76. B. Aman, G. Ciobanu: Typed Membrane Systems. Lecture Notes in Computer Science, vol. 5957, 169-181, 2010.
  77. G. Berry, G. Boudol: The Chemical Abstract Machine. Theoretical Computer Science, vol. 96, 217-248, 1992.
  78. I. Eidhammer, I. Jonassen, W. Taylor: Structure Comparison and Structure Patterns, Journal of Computational Biology, vol.7, 685-716, 2000.
  79. D.E. Leocadio, A.R. Kunselman, T. Cooper, J.H. Barrantes, J.C. Trussell: Anatom- ical and Histological Equivalence of the Human, Canine, and Bull Vas Deferens, The Canadian Journal of Urology, vol.18, 5699-5704, 2011.
  80. G. Pȃun: Some Open Problems Collected During 7th BWMC. Proceedings of the Seventh Brainstorming Week on Membrane Computing, vol. 2, 197-206, 2009.
  81. B. Russell: The Principles of Mathematics, vol.I, Cambridge University Press, 1903.
  82. J. Wells: The Essence of Principal Typings. LNCS 2380, Springer, 913-925, 2002. References
  83. A. Alhazov, L. Pan, Gh. Pȃun, Trading Polarizations for Labels in P Systems with Active Membranes, Acta Informatica, 41, 111 -144, 2004.
  84. A. Alhazov, D. Sburlan, Static Sorting P Systems. In [6], 215 -252, 2006.
  85. O. Andrei, G. Ciobanu, D. Lucanu, A Rewriting Logic Framework for Operational Semantics for Membrane Systems, Theoretical Computer Science, 373, 163 -181, 2007.
  86. R. Barbuti, A. Maggiolo-Schettini, P. Milazzo, S. Tini, Membrane Systems Working in Generating and Accepting Modes: Expressiveness and Encodings. In M. Gheorghe, T. Hinze, Gh. Pȃun, G. Rozenberg, A. Salomaa, eds., Membrane Computing, 11th International Conference, CMC2010, Jena, Germany, August 2010, LNCS 6501, 103 -118.
  87. R. Ceterchi, C. Martín-Vide, P Systems with Communication for Static Sorting. In M. Cavaliere, C. Martín-Vide, Gh. Pȃun, eds., Pre-Proceedings of Brainstorming Week on Membrane Computing, Tarragona, February 2003, Technical Report no 26, Rovira i Virgili Univ., Tarragona, 2003.
  88. G. Ciobanu, Gh. Pȃun, M. J. Pérez-Jiménez, eds., Applications of Membrane Com- puting, Springer, 2006.
  89. D. Díaz-Pernil, M. A. Gutiérrez-Naranjo, M. J. Pérez-Jiménez, A Uniform Family of TissueP Systems with Cell Division Solving 3-COL in a Linear Time, Theoretical Computer Science, 404, 76 -87, 2008.
  90. R. Nicolescu, M. J. Dinneen, Y.-B. Kim, Structured Modelling with Hyperdag P Systems: Part A. In R. Gutiérrez-Escudero, M. A Gutiérrez-Naranjo, Gh. Pȃun, I. Pérez-Hurtado, eds., Membrane Computing, Seventh Brainstorming Week, BWMC 2009, Sevilla, Spain, February 2009, Universidad de Sevilla, 85 -107, 2009.
  91. The P-lingua Website: http://www.p-lingua/wiki/index.php/Main Page. 13 Membrane Algorithms Gexiang Zhang School of Electrical Engineering Southwest Jiaotong University Chengdu, P.R. China zhdxdylan@126.com The possible interplay between membrane computing and evolutionary com- putation may produce three kinds of research topics: References
  92. G. Zhang, C. Liu, M. Gheorghe, F. Ipate: Solving satisfiability problems with mem- brane algorithms. Proc. Fourth International Conference on Bio-lnspired Computing: Theories and Applications, 2009, 29-36.
  93. G. Zhang, C. Liu, H. Rong: Analyzing radar emitter signals with membrane algo- rithms. Mathematical and Computer Modelling, 2010,52(11-12), 1997-2010.
  94. X. Huang, G. Zhang, F. Ipate: Evolutionary design of a simple membrane system. Proceedings of CMC, 2011.
  95. V. Manca, R. Lombardo: Computing with multi-membranes. In Proc. CMC 2011, 347-364.
  96. V. Manca, L. Marchetti: Metabolic approximation of real periodical functions. J. Logic and Algebraic Programming, 79 (2010), 363-373.
  97. V. Manca, L. Marchetti: Log-gain stoichiometricstepwise regression for MP systems. Int. J. Foundations of Computer Science, 22 (2011), 97-106.
  98. V. Manca, L. Marchetti: Paper in progress, 2011.
  99. Unraveling Oscillating Structures by Means of P Systems Thomas Hinze 1,2
  100. Saxon University of Cooperative Education Dresden, Germany thomas.hinze@uni-jena.de 15.1 Motivation Endogenous oscillations have been identified to be essential for the function of numerous systems found in biology as well as engineering [1, 2, 26]. A common property of these systems lies in their necessity to synchronize and coordinate References
  101. U. Alon. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall, 2006
  102. J. Aschoff. A survey on biological rhythms. Biological Rhythms 4:3-10, 1981
  103. B.W. Bequette. Process control: modeling, design, and simulation. Prentice Hall, 2003
  104. R.E. Best. Phase-locked loops: design, simulation, and applications. McGraw-Hill, 2007
  105. B. Botti, C. Youan (Eds.). Chronopharmaceutics. Science and technology for biolog- ical rhythm guided therapy and prevention of diseases. John Wiley & Sons, 2009
  106. K.A. Connors. Chemical Kinetics. VCH Publishers, Weinheim, 1990
  107. F. Fontana, V. Manca. Discrete solutions to differential equations by metabolic P systems. Theoretical Computer Science 372(2-3):165-182, 2007
  108. B.C. Goodwin. Oscillatory behaviour in enzymatic control processes. Advanced En- zyme Regulation 3:425-438, 1965
  109. G. Gruenert, B. Ibrahim, T. Lenser, M. Lohel, T. Hinze, P. Dittrich. Rule-based spatial modeling with diffusing, geometrically constrained molecules. BMC Bioinfor- matics 11:307, 2010
  110. B.A. Hawkins, H.V. Cornell (Eds.). Theoretical Approaches to Biological Control. Cambridge University Press, 1999
  111. T. Hinze, T. Lenser, P. Dittrich. A Protein Substructure Based P System for De- scription and Analysis of Cell Signalling Networks. In H.J. Hoogeboom et al. (Eds.). LNCS 4361: 409-423, Springer Verlag, 2006
  112. T. Hinze, R. Fassler, T. Lenser, P. Dittrich. Register Machine Computations on Binary Numbers by Oscillating and Catalytic Chemical Reactions Modelled using Mass-Action Kinetics. International Journal of Foundations of Computer Science 20(3):411-426, 2009
  113. T. Hinze, R. Fassler, T. Lenser, N. Matsumaru, P. Dittrich. Event-Driven Metamor- phoses of P Systems. In D. Corne et al. (Eds.). LNCS 5391: 231-245, Springer Verlag, 2009
  114. T. Hinze, T. Lenser, G. Escuela, I. Heiland, S. Schuster. Modelling Signalling Net- works with Incomplete Information about Protein Activation States: A P System Framework of the KaiABC Oscillator. In G. Pȃun et al. (Eds.). LNCS 5957 :316-334, Springer Verlag, 2010
  115. T. Hinze, M. Schumann, C. Bodenstein, I. Heiland, S. Schuster. Biochemical Fre- quency Control by Synchronisation of Coupled Repressilators: An In-silico Study of Modules for Circadian Clock Systems. Computational Intelligence and Neuroscience 2011:e262189, 2011
  116. T. Hinze, C. Bodenstein, I. Heiland, S. Schuster. Capturing Biological Frequency Control of Circadian Clocks by Reaction System Modularization. ERCIM News 85:27-29, 2011
  117. T. Hinze, C. Bodenstein, B. Schau, I. Heiland, S. Schuster. Chemical Analog Com- puters for Clock Frequency Control Based on P Modules. In M. Gheorghe et al. (Eds.). Proceedings CMC12, LNCS, Springer Verlag, 2011, to appear
  118. T. Kapitaniak (Ed.). Chaotic Oscillators: Theory and Applications. World Scientific Pub. Co., 1992
  119. Y. Kuramoto. Chemical Oscillations, Waves, and Turbulences. Springer, 1984
  120. T. Lenser, T. Hinze, B. Ibrahim, P. Dittrich. Towards Evolutionary Network Re- construction Tools for Systems Biology. In E. Marchiori et al. (Eds.). LNCS 4447: 132-142, Springer Verlag, 2007
  121. V. Manca, L. Bianco, F. Fontana. Evolution and oscillation in P systems: Applica- tions to biological phenomena. In G. Mauri et al. (Eds.). Lecture Notes in Computer Science 3365:63-84, Springer Verlag, 2005
  122. D. Morgan. The Cell Cycle: Principles of Control. Oxford University Press, 2006
  123. T. Mori, D.R. Williams, M.O. Byrne, X. Qin, M. Egli, H.S. Mchaourab, P.L. Stew- art, C.H. Johnson. Elucidating the ticking of an in vitro circadian clockwork. PLoS Biology 5(4):841-853, 2007
  124. T. Pavlidis. Biological Oscillators: Their Mathematical Analysis. Academic Press, 1974
  125. P. Ruoff, M. Vinsjevik, C. Monnerjahn, L. Rensing. The Goodwin Oscillator: On the Importance of Degradation Reactions in the Circadian Clock. Journal of Biological Rhythms 14(6):469-479, 1999
  126. S. Schuster, M. Marhl, T. Hoefer. Modelling of simple and complex calcium oscilla- tions. European Journal of Biochemistry 269:1333-1355, 2002
  127. V.K. Sharma, A. Joshi. Clocks, genes, and evolution. The evolution of circadian organization. In V. Kumar (Ed.). Biological Rhythms, p. 5-23, Springer Verlag, 2002 References
  128. Bandyopadhyay, A., Fujita, D., Pati, R., Architecture of a Massively Parallel Pro- cessing Nano-Brain Operating 100 Billion Molecular Neurons Simultaneously, Inter- national Journal of Nanotechnology and Molecular Computation 1 (2009), pp. 50-80.
  129. Bohte, S.M., Spiking Neural Networks, Professorschrift, Leiden University 2003.
  130. Booij, O., Temporal Pattern Classification using Spiking Neural Networks, M.Sc. Thesis, Amsterdam University 2004.
  131. Booij, O., Hieu tat Nguyen, A gradient descent rule for spiking neurons emitting multiple spikes, in: Applications of Spiking Neural Networks, ed. S.M. Bohte and J.N. Kok, Information Processing Letters, Amsterdam 2005.
  132. Ceterchi, R., Tomescu, I.A., Spiking Neural P systems-a Natural Model for Sorting Networks, in: Proceedings of Sixth Brainstorming Week on Membrane Computing, Sevilla, February 4-8, 2008, ed. D. Diaz-Perenil et al., RGNC Report 01/2008, Sevilla University Fenix Editora 2008, pp. 93-105.
  133. Geary, D., The Origin of Mind: Evolution of Brain, Cognition, and General Intelli- gence, American Psychological Association 2005.
  134. Gerstner, W., Population Dynamics of Spiking Neurons: Fast Transients, Asyn- chronous States, and Locking, Neural Computation 12 (2000), pp. 43-89.
  135. Gutiérez-Naranjo, M.A., Pérez-Jiménez, M.J., A spiking neural P systems based model for Hebbian learning, in: Proceedings of 9th Workshop on Membrane Com- puting, Edinburgh, July 28 -July 31, 2008, ed. P. Frisco et al., Technical Report HW-MASC-TR-0061, School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK, 2008, pp. 189-207.
  136. Ionescu, M., Sburlan, D., Some Applications of Spiking Neural P Systems, in: Pro- ceedings of the 8th Workshop on Membrane Computing, Thessaloniki, June 25-28, 2007, ed. Eleftherakis et al., South-East European Research Centre 2007, pp. 383- 394.
  137. Ionescu, M., Pȃun, Gh., Yokomori, Y., Spiking neural P systems, Fund. Inform. 71 (2006), pp. 279-308.
  138. Kasiński, A., Ponulak, F., Comparison of Supervised Learning Methods for Spike Time Coding in Spiking Neural Networks, Int. J. Appl. Math. Comput. Sci. 16 (2006), pp. 101-113.
  139. Knoblauch, A., Palm. G., Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales, Biol. Cybern. 87 (2002), pp. 168-184.
  140. MacDonald, K., Chiappe, D., Review of [6] in Human Ethology Bulletin 21:2 (2006), pp. 14-18.
  141. Meftah, B., Benyettou, A., Lezoray, O., Qingxiang, W., Image Clustering with Spiking Neuron Network, in: World Congress on Computational Intelligence, International Joint Conference on Neural Networks, Hong-Kong 2008.
  142. Moore, S.C., Back-propagation in spiking neural networks, M.Sc. Thesis, University of Bath 2002, http://www.simonchristianmoore.co.uk/Thesis4.html.
  143. Natschläger, T., Ruf, B., Spatial and temporal pattern analysis via spiking neurons, Network: Comp. Neural Systems 9 (1998), pp. 319-332.
  144. Pȃun, Gh., Pérez-Jiménez, M.J., Spiking neural P systems. Recent results, research topics, presented at the 6th Brainstorming Week on Membrane Computing, Sevilla 2008, web page http://psystems.disco.unimib.it/download/leidenGR65.pdf
  145. Ruf, B., Computing and Learning with Spiking Neurons-Theory and Simulation, Doctoral Thesis, Technische Universität Graz 1998.
  146. J. Carnero, D. Díaz-Pernil, M.A. Gutiérrez-Naranjo: Designing tissue-like P systems for image segmentation on parallel architectures. In M.A. Martínez del Amor, Gh. Pȃun, I. Pérez-Hurtado de Mendoza, F.J. Romero-Campero, L.V. Cabrera, eds., Ninth Brainstorming Week on Membrane Computing, pages 43-62, Sevilla, Spain, 2011. Fénix Editora.
  147. R. Ceterchi, R. Gramatovici, N. Jonoska, K.G. Subramanian: Tissue-like P systems with active membranes for picture generation. Fundamenta Informaticae, 56(4):311- 328, 2003.
  148. R. Ceterchi, M. Mutyam, Gh. Pȃun, K.G. Subramanian: Array-rewriting P systems. Natural Computing, 2(3):229-249, 2003.
  149. J. Chao, J. Nakayama: Cubical singular simplex model for 3D objects and fast com- putation of homology groups. In 13th International Conference on Pattern Recog- nition (ICPR'96), volume IV, pages 190-194, Los Alamitos, CA, USA, 1996. IEEE Computer Society, IEEE Computer Society.
  150. H.A. Christinal, D. Díaz-Pernil, M.A. Gutiérrez-Naranjo, M.J. Pérez-Jiménez: Thresholding of 2D images with cell-like P systems. Romanian Journal of Infor- mation Science and Technology (ROMJIST), 13(2):131-140, 2010.
  151. H.A. Christinal, D. Díaz-Pernil, P. Real: Segmentation in 2D and 3D im- age using tissue-like P system. In E. Bayro-Corrochano, J.-O. Eklundh, eds., Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Guadalajara, Jalisco, Mexico, November 15-18, 2009. Proceedings, LNCS 5856, pages 169-176, Springer, Berlin, 2009.
  152. H.A. Christinal, D. Díaz-Pernil, P. Real: Using membrane computing for obtaining homology groups of binary 2D digital images. In P. Wiederhold, R.P. Barneva, eds., Combinatorial Image Analysis 13th International Workshop, IWCIA 2009, Playa del Carmen, Mexico, November 24-27, 2009. Proceedings, LNCS 5852, pages 383-396, Berlin, 2009. Springer.
  153. H.A. Christinal, D. Díaz-Pernil, P. Real: P systems and computational algebraic topology. Journal of Mathematical and Computer Modelling, 52(11-12):1982 -1996, December 2010. The BIC-TA 2009 Special Issue, International Conference on Bio- Inspired Computing: Theory and Applications.
  154. H.A. Christinal, D. Díaz-Pernil, P. Real: Region-based segmentation of 2D and 3D images with tissue-like P systems. Pattern Recognition Letters, 32(16):2206 -2212, 2011. Advances in Theory and Applications of Pattern Recognition, Image Processing and Computer Vision.
  155. K.S. Dersanambika, K. Krithivasan: Contextual array P systems. International Journal of Computer Mathematics, 81(8):955-969, 2004.
  156. D. Díaz-Pernil, M.A. Gutiérrez-Naranjo, H. Molina-Abril, P. Real: A bio-inspired software for segmenting digital images. In A.K. Nagar, R. Thamburaj, K. Li, Zhuo Tang, R. Li, eds., Proceedings of the 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications BIC-TA, volume 2, pages 1377 -1381, Beijing, China, 2010. IEEE Computer Society.
  157. D. Díaz-Pernil, M.A. Gutiérrez-Naranjo, H. Molina-Abril, P. Real: Designing a new software tool for digital imagery based on P systems. Natural Computing, pages 1-6, 2011. 10.1007/s11047-011-9287-4.
  158. D. Díaz-Pernil, M.A. Gutiérrez-Naranjo, P. Real, V. Sánchez-Canales: Computing homology groups in binary 2D imagery by tissue-like P systems. Romanian Journal of Information Science and Technology (ROMJIST), 13(2):141-152, 2010.
  159. M. Egmont-Petersen, D. de Ridder, H. Handels: Image processing with neural net- works -a review. Pattern Recognition, 35(10):2279-2301, 2002.
  160. C. Ferretti, G. Mauri, C. Zandron: P systems with string objects. In Gh. Pȃun, G. Rozenberg, A. Salomaa, eds., The Oxford Handbook of Membrane Computing, pages 168 -197. Oxford University Press, Oxford, England, 2010.
  161. D. Freedman, C. Chen: Algebraic topology for computer vision. Science And Tech- nology, 2009.
  162. G. Gimel'farb, R. Nicolescu, S. Ragavan: P systems in stereo matching. In P. Real, D. Diaz-Pernil, H. Molina-Abril, A. Berciano, W. Kropatsch, eds., Computer Analysis of Images and Patterns, LNCS 6855, pages 285-292. Springer Berlin, 2011.
  163. G.L. Gimel'farb: Probabilistic regularisation and symmetry in binocular dynamic programming stereo. Pattern Recognition Letters, 23(4):431-442, 2002.
  164. S.N. Krishna, R. Rama, K. Krithivasan: P systems with picture objects. Acta Cybernetica, 15(1):53-74, 2001.
  165. F. Peña-Cantillana, D. Díaz-Pernil, A. Berciano, M.A. Gutiérrez-Naranjo: A parallel implementation of the thresholding problem by using tissue-like P systems. In P. Real, D. Díaz-Pernil, H. Molina-Abril, A. Berciano, W.G. Kropatsch, eds., CAIP (2), LNCS 6855, pages 277-284. Springer, 2011.
  166. F. Peña-Cantillana, D. Díaz-Pernil, H.A. Christinal, M.A. Gutiérrez-Naranjo: Im- plementation on CUDA of the smoothing problem with tissue-like P systems. Inter- national Journal of Natural Computing Research, 2(3):25-34, 2011.
  167. Gh. Pȃun: Computing with membranes. Technical Report 208, Turku Centre for Computer Science, Turku, Finland, November 1998.
  168. Gh. Pȃun: Computing with membranes. Journal of Computer and System Sciences, 61(1):108-143, 2000. See also [22].
  169. P.L. Rosin: Training cellular automata for image processing. IEEE Transactions on Image Processing, 15(7):2076-2087, 2006.
  170. P.J. Selvapeter, W. Hordijk: Cellular automata for image noise filtering. In NaBIC, pages 193-197. IEEE, 2009.
  171. L.G. Shapiro, G.C. Stockman: Computer Vision. Prentice Hall PTR, Upper Saddle River, NJ, USA, 2001.
  172. S.M. Trimberger: Field-Programmable Gate Array Technology. Kluwer Academic Publishers, Norwell, MA, USA, 1994.
  173. Y.T. Zhou, R. Chellappa: Artificial neural networks for computer vision. Research notes in neural computing. Springer-Verlag, 1992.
  174. NVIDIA Corporation. NVIDIA CUDA TM Programming Guide. http://www.nvidia.com/object/cuda home new.html.
  175. A. Ehrenfeucht, G. Rozenberg: Basic notions of reaction systems, Proc. DLT 2004 (C.S. Calude, E. Calude, M.J. Dinneen, eds.), LNCS 3340, Springer, 2004, 27-29.
  176. A. Ehrenfeucht, G. Rozenberg: Reaction systems. Fundamenta Informaticae, 75 (2007), 263-280.
  177. A. Ehrenfeucht, G. Rozenberg: Events and modules in reaction systems. Theoretical Computer Sci., 376 (2007), 3-16.
  178. A. Ehrenfeucht, G. Rozenberg: Introducing time in reaction systems. Theoretical Computer Sci., 410 (2009), 310-322.
  179. A. Ehrenfeucht, G. Rozenberg: Reaction systems. A model of computation inspired by biochemistry. Proc. DLT 2010 (Y. Gao et al., eds.), LNCS 6224, Springer, 2010, 1-3.
  180. R. Freund, L. Kari, P. Sosik: Computationally universal P systems without priorities: two catalysts are sufficient. Theoretical Computer Sci., 330 (2005), 251-266.
  181. R. Freund, M. Oswald: Partial halting in P systems. Intern. J. Foundations of Com- puter Sci., 18 (2007), 1215-1225.
  182. P. Frisco: Computing with Cells. Advances in Membrane Computing. Oxford Univer- sity Press, 2008.
  183. J. Kleijn, M. Koutny: Membrane systems with qualitative evolution rules, Fundaenta Informaticae, to appear.
  184. Gh. Pȃun: Towards fypercomputations (in membrane computing). LNCS, Springer, to appear.
  185. Gh. Pȃun, M.J. Pérez-Jiménez: Towards Bridging Two Cell-Inspired Models: P Sys- tems and R Systems. Submitted, 2011.
  186. G. Rozenberg, A. Salomaa: The Mathematical Theory of L Systems. Academic Press, New York, 1980.

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