Skip to main content
Log in

An interactive timeline of simulators in membrane computing

Depicting two decades of evolution in the simulation of P systems

  • Survey Paper
  • Published:
Journal of Membrane Computing Aims and scope Submit manuscript

Abstract

As with any fast-emerging research front in computer science, the proliferation of theoretical and practical results within Membrane computing since its appearance in 1998 was astonishing. As a consequence, it became necessary during the subsequent years to produce several surveys collecting the main achievements from a theoretical point of view, along with some specific surveys about simulation tools for this paradigm. As the discipline has reached a certain degree of maturity, more practical applications have arisen, and new collective works are summarising the new software products appeared. However, while these recapitulation efforts remain useful for details about new simulators, they cannot act as exhaustive updated listings, as they become obsolete as soon as new tools are developed. Thus, we considered that it was necessary to provide an interactive tool showing an updated timeline (https://www.gcn.us.es/SimulationMC) about the simulation of the computational devices of membrane computing (a.k.a P systems), aiming to stay updated whenever any new practical work comes out in the discipline. This paper recalls the main stages and milestones within the evolution of simulation tools for different types and variants of P systems, along with their main related applications. In addition, it describes the interactive web tool with the timeline mentioned, where all the references related here have been incorporated. Unlike other survey papers, it is the intent of this work to reinforce this initial collective effort with the web endpoint kept alive and updated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

Books and collective volumes

  1. Păun, G. H. (2002). Membrane computing. An introduction. New York: Springer.

    Book  MATH  Google Scholar 

  2. Ciobanu, G., Păun, Gh, & Pérez-Jiménez, M. J. (2006). Applications of membrane computing. New York: Springer.

    Google Scholar 

  3. Păun, G. H., Rozenberg, G., & Salomaa, A. (2010). The oxford handbook of membrane computing. New York: Oxford University Press.

    Book  MATH  Google Scholar 

  4. Florea, A. G., & Buiu, C. (2017). Membrane computing for distributed control of robotic swarms: Emerging research and opportunities. USA: IGI Global.

    Book  Google Scholar 

  5. Zhang, G., Pérez-Jiménez, M. J., & Gheorghe, M. (2017). Real-life applications with membrane computing. Series: Emergence, complexity and computation, 25. New York: Springer.

    Book  Google Scholar 

Surveys

  1. Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2006). Available membrane computing software. In G. Ciobanu, G. Păun, & M. J. Pérez-Jiménez (Eds.), Applications of membrane computing (pp. 411–436). Heidelberg: Springer.

    Google Scholar 

  2. Díaz-Pernil, D., Graciani-Díaz, C., Gutiérrez-Naranjo, M. A., Pérez-Hurtado, I., & Pérez-Jiménez, M. J. (2010). Software for P systems. In Gh Păun, G. Rozenberg, & A. Salomaa (Eds.), The oxford handbook of membrane computing (pp. 437–454). Oxford: Oxford University Press.

    Google Scholar 

  3. Raghavan, S., & Chandrasekaran, K. (2016). Tools and simulators for membrane computing—A literature review. In: Gong M., Pan L., Song T., Zhang G. (eds.) Bio-inspired computing—Theories and applications. BIC-TA 2016. Communications in Computer and Information Science, 681, Springer, Singapore, pp. 249–277.

  4. Martínez-del-Amor, M. A., García-Quismondo, M., Macías-Ramos, L. F., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez, M. J. (2015). Simulating P systems on GPU devices: A survey. Fundamenta Informaticae, IOS Press, 136, 269–284.

    MathSciNet  MATH  Google Scholar 

  5. Martínez-del-Amor, M. A., Macías-Ramos, L. F., Valencia-Cabrera, L., & Pérez-Jiménez, M. J. (2016). Parallel simulation of population dynamics P systems: Updates and roadmap. Natural Computing, 15(4), 565–573.

    Article  MathSciNet  MATH  Google Scholar 

  6. Zhang, G., Pérez-Jiménez, M. J., & Gheorghe, M. (2017). Data modeling with membrane systems: Applications to real ecosystems. Real-life applications with membrane computing. Springer International Publishing, pp. 259–355.

  7. Valencia-Cabrera, L., Orellana-Martín, D., Martínez-del-Amor, M. A., & Pérez-Jiménez, M. J. (2017). From super-cells to robotic swarms: Two decades of evolution in the simulation of P systems. Bulletin of the International Membrane Computing Society, 4, 65–87.

    Google Scholar 

Extensive bibliography

  1. Păun, Gh. (1998). Computing with membranes. Turku Center for Computer Science, TUCS Technical report, 208, 1–42.

    Google Scholar 

  2. Păun, Gh. (2000). Computing with membranes. Journal of Computer and System Sciences, 61(1), 108–143.

    Article  MathSciNet  MATH  Google Scholar 

  3. Păun, Gh. (2001). P systems with active membranes: Attacking NP-complete problems. Journal of Automata, Languages and Combinatorics, 6, 75–90.

    MathSciNet  MATH  Google Scholar 

  4. Suzuki, Y., & Tanaka, H. (2000). On a LISP implementation of a class of P systems. Romanian Journal of Information Science and Technology, 3(2), 173–186.

    Google Scholar 

  5. Suzuki, Y., Fujiwara, Y., Tanaka, H., & Takabayashi, J. (2001). Artificial life applications of a class of P systems: Abstract rewriting systems on multisets. In Calude, C.S., Păun, Gh., Rozenberg, G., Salomaa, A. (eds.) Multiset Processing. Mathematical, Computer Science, and Molecular Computing Points of View. Lecture Notes in Computer Science, 2235, Springer, 299–346.

  6. Maliţa, M. (2000). Membrane computing in prolog. In: Pre-Proceedings of the Workshop on Multiset Processing, Curtea de Arges, Romania, TR 140, CDMTCS, University of Auckland, pp. 159–175.

  7. Balbontín-Noval, D., Pérez-Jiménez, M. J., & Sancho-Caparrini, F. (2003). A MzScheme implementation of transition P systems. In: Păun, G., Rozenberg, G., Salomaa, A., Zandron, C. (eds.) Lecture Notes in Computer Science, Springer, Heidelberg, 2597, pp. 58–73.

  8. Pérez-Jiménez, M. J., & Sancho-Caparrini, F. (2002). A formalization of transition P systems. Fundamenta Informaticae, 49, 261–272.

    MathSciNet  MATH  Google Scholar 

  9. Arroyo, F., Luengo, C., Baranda, A. V., & Mingo, L. (2003). A software simulation of transition P systems in Haskell. In G. Păun, G. Rozenberg, A. Salomaa, & C. Zandron (Eds.), Lecture notes in computer science (Vol. 2597, pp. 19–32). Heidelberg: Springer.

    MATH  Google Scholar 

  10. Baranda, A.V., Castellanos, J., Arroyo, F., & Gonzalo, R. (2000). Data structures for implementing transition P systems in silico. In: Pre-Proceedings of the Workshop on Multiset Processing, Curtea de Arges, Romania, TR 140, CDMTCS, University of Auckland, pp. 21–34.

  11. Arroyo, F., Baranda, A. V., Castellanos, J., Luengo, C., & de Mingo, L. F. (2001). A Recursive Algorithm for Describing Evolution in Transition P Systems. In Pre-Proceedings of Workshop on Membrane Computing, Curtea de Arges, Romania, Technical report 17/01 of Research Group on Mathematical Linguistics, Rovira i Virgili University, Tarragona, Spain, 19–30.

  12. Arroyo, F., Baranda, A. V., Castellanos, J., Luengo, C., & de Mingo, L. F. Structures and Bio-Language to simulate transition P systems on digital computers. In C.S. Calude, Gh. Păun, G. Rozenberg, A. Salomaa, (eds.) Multiset processing. Mathematical, Computer Science and Molecular Computing Points of View, Lecture Notes in Computer Science, 2235, pp. 1–16.

  13. Baranda, A. V., Castellanos, J., Gonzalo, R., Arroyo, F., & de Mingo, L. F. (2001). Data structures for implementing transition P systems in silico. Romanian Journal of Information Science and Technology, 4(1–2), 21–32.

    Google Scholar 

  14. Baranda, A. V., Castellanos, J., Arroyo, F., & Gonzalo, R. (2002). Towards an electronic implementation of membrane computing: A formal description of nondeterministic evolution in transition P systems. In Jonoska, N., Seeman, N. C. (eds.) Proceedings of DNA-Based Computers, Tampa, Florida, LNCS, 2340, 350–359.

  15. Nepomuceno-Chamorro, I. A. (2004). A Java Simulator for basic transition P systems. In Păun, Gh., Riscos-Núñez, A., Romero-Jiménez, A., Sancho-Caparrini, F. (eds.) Proceedings of the Second Brainstorming Week on Membrane Computing, Sevilla, Spain, Report RGNC 01/04, 309–315.

  16. Ciobanu, G., & Wenyuan, G. (2003). A Parallel Implementation of Transition P Systems. In Alhazov, A., Martín-Vide, C. Păun, Gh. (eds.) Pre-Proceedings of the Workshop on Membrane Computing, Tarragona, Spain, 2003, Report RGML 28/03, 169–184.

  17. Ciobanu, G., & Wenyuan, G. (2004). P Systems Running on a Cluster of Computers. In Martín-Vide, C., Păun, Gh., Rozenberg, G., Salomaa, A. (eds.) Lecture Notes in Computer Science, 2933, 123–139.

  18. Syropoulos, A., Mamatas, E.G., Allilomes, P.C., & Sotiriades, K.T. (2004). A Distributed Simulation of Transition P Systems. In Martín-Vide, C., Păun, Gh., Rozenberg, G., Salomaa, A. (eds.) Lecture Notes in Computer Science, 2933, 357–368.

  19. Ciobanu, G., & Paraschiv, D. (2002). P system software simulator. Fundamenta Informaticae, 49(1–3), 61–66.

    MATH  Google Scholar 

  20. Pérez-Jiménez, M.J., & Romero-Campero, F. (2004). A CLIPS Simulator for Recognizer P Systems with Active Membranes. In Păun, Gh., Riscos-Núñez, A., Romero-Jiménez, A., Sancho-Caparrini, F. (eds.) Proceedings of the Second Brainstorming Week on Membrane Computing, Sevilla, Spain, Report RGNC 01/04, 2004, 387–413.

  21. Pérez-Jiménez, M. J., & Romero-Campero, F. J. (2004). An efficient family of P systems for packing items into bins. Journal of Universal Computer Science, 10(5), 650–670.

    MathSciNet  Google Scholar 

  22. Pérez-Jiménez, M. J., & Romero-Campero, F. J. (2005). Attacking the Common algorithmic problem by recognizer P systems. Lecture Notes in Computer Science, 3354, 304–315.

    Article  MathSciNet  MATH  Google Scholar 

  23. Cordón-Franco, A., Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Sancho-Caparrini, F. (2004). A prolog simulator for deterministic P systems with active membranes. New Generation Computing, 22(4), 349–364.

    Article  MATH  Google Scholar 

  24. Cordón-Franco, A., Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., Riscos-Núñez, A., & Sancho-Caparrini, F. (2004). Implementing in prolog an effective cellular solution to the knapsack problem. In Martín-Vide, C., Păun, Gh., Rozenberg, G., Salomaa, A. (eds.) Lecture Notes in Computer Science, 2933, 140–152.

  25. Cordón-Franco, A., Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., Riscos-Núñez, A., & Sancho-Caparrini, F. (2005). Cellular solutions of some numerical NP-complete problems: A prolog implementation. In M. Gheorghe (Ed.), Molecular computational models: Unconventional approaches (pp. 115–149). Calgary: Idea Group Inc.

    Chapter  Google Scholar 

  26. Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2005). A fast P system for finding balanced 2-partition. Soft Computing, 9, 673–678.

    Article  MATH  Google Scholar 

  27. Ciobanu, G., Păun, G. H., & Ştefănescu, G. H. (2003). Sevilla carpets associated with P systems. In Cavaliere, M., Martín-Vide, C., Păun, G. H. (eds.). In: Proceedings of the Brainstorming Week on Membrane Computing, Tarragona, Spain, 2003, Report RGML 26/03, 135–140.

  28. Riscos-Núñez. (2004). Cellular programming: Efficient resolution of numerical NP-complete problems. PhD Thesis, University of Seville.

  29. Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2005). On descriptive complexity of P systems. Lecture Notes in Computer Science, 3365, 320–330.

    Article  MATH  Google Scholar 

  30. Binder, A., Freund, R., Lojka, G., & Oswald, M. (2004). Implementation of Catalytic P Systems. Proceedings of CIAA 2004, Ninth International Conference on Implementation and Application of Automata, Kingston, Canada, 2004, 24–33.

  31. Alhazov, A. (2005). Maximally Parallel Multiset-Rewriting Systems: Browsing the Configurations. Proceeding of the Third Brainstorming Week on Membrane Computing, Sevilla, 2005, RGNC Report 01/2005, 1–10.

  32. Margenstern, M., Rogozhin, V., Rogozhin, Yu, & Verlan, S. (2004). About P Systems with Minimal Symport/Antiport Rules and Four Membranes. In G. Mauri, Gh. Păun, C. Zandron, eds.: Pre-Proceedings of the Workshop on Membrane Computing WMC5, Universitá di Milano-Bicocca, Italy, 2004, 283–294.

  33. Alhazov, A., Margenstern, M., Rogozhin, V., Rogozhin, Yu., & Verlan, S. (2005). Communicative P systems with minimal cooperation. Lecture Notes in Computer Science, 3365, 161–177.

    Article  MATH  Google Scholar 

  34. Georgiou, A. (2003). Sub-LP systems a computational model for plant simulation. MSc Dissertation, University of Sheffield.

  35. Georgiou, A., & Gheorghe, M. (2003). Generative devices used in graphics. In Alhazov, A. et al (eds.) Pre-proceedings of the Workshop on Membrane Computing Technical Report 28/03, Universitat Rovira i Virgili, Tarragona, 266–272.

  36. Georgiou, A., Gheorghe, M., & Bernardini, F. (2006). Membrane-based devices used in computer graphics. In G. Ciobanu, Gh Păun, & M. J. Pérez-Jiménez (Eds.), Applications of Membrane Computing (pp. 253–282). New York: Springer.

    Google Scholar 

  37. Nicolau, D. V, Jr., Solana, G., Fulga, F., & Nicolau, D. V, Sr. (2002). A C library for simulating P systems. Fundamenta Informaticae, 49(1–3), 241–248.

    MATH  Google Scholar 

  38. Petreska, B., & Teuscher, C. (2004). A reconfigurable hardware membrane system. In: Martín-Vide, C., Păun, G. H., Rozenberg, G., Salomaa, A. (eds.) Lecture Notes in Computer Science, 2933, 269–285.

  39. Madhu, M., Murty, V.S., & Krithivasan, K. (2002). A hardware realization of P systems with carriers. Poster presentation at the Eight International Conference on DNA based Computers, Hokkaido University, Sapporo Campus, Japan, June 10–13.

  40. Ardelean, I. I., & Cavaliere, M. (2003). Modelling biological processes by using a probabilistic P system software. Natural Computing, 2(2), 173–197.

    Article  MATH  Google Scholar 

  41. Cavaliere, M. (2003). Evolution-communication P systems. In G. Păun, G. Rozenberg, A. Salomaa, & C. Zandron (Eds.), Lecture notes in computer science (pp. 13–145). Heidelberg: Springer.

    Google Scholar 

  42. Cavaliere, M., & Ardelean, I. I. (2006). Modeling respiration in bacteria and respiration/photosynthesis interaction in cyanobacteria using a P system simulator. In G. Ciobanu, G. Păun, & M. J. Pérez-Jiménez (Eds.), Applications of membrane computing (pp. 129–158). Heidelberg: Springer.

    Google Scholar 

  43. Bianco, L., & Castellini, A. (2007). Psim: A computational platform for metabolic P systems. Lecture Notes in Computer Science, 4860, 1–20.

    Article  MATH  Google Scholar 

  44. Bianco, L., Manca, V., Marchetti, L., & Petterlini, M. (2008). Psim: a simulator for biomolecular dynamics based on P systems. In: 2007 IEEE Congress on Evolutionary Computation, IEEE XPlore, 883–887.

  45. Bianco, L., Fontana, F., Franco, G., & Manca, V. (2006). P systems for biological dynamics. In G. Ciobanu, G. Păun, & M. J. Pérez-Jiménez (Eds.), Applications of membrane computing (pp. 83–128). Heidelberg: Springer.

    Google Scholar 

  46. Nepomuceno, I., Nepomuceno, J.A., Romero-Campero, F.J., & Gutiérrez-Naranjo, M.A. (2005). A tool for using the SBML format to represent P systems which model biological reaction networks. In Riscos-Núñez, A., Romero-Campero, F.J., Sburlan, D. (eds.) Third brainstorming week on membrane computing, Fénix Editora, 219–228.

  47. Pérez-Jiménez, M. J., & Romero-Campero, F. J. (2005). A study of the robustness of the EGFR signalling cascade using continuous membrane systems. Lecture Notes in Computer Science, 3561, 268–278.

    Article  Google Scholar 

  48. Cheruku, S., Păun, A., Romero-Campero, F. J., Pérez-Jiménez, M. J., & Ibarra, O. H. (2007). Simulating FAS-induced apoptosis by using P systems. Progress in Natural Science, 17, 424–431.

    Article  MathSciNet  MATH  Google Scholar 

  49. Romero-Campero, F. J., & Pérez-Jiménez, M. J. (2008). Modelling gene expression control using P systems: The Lac operon, a case study. Biosystems, 91, 438–457.

    Article  Google Scholar 

  50. Romero-Campero, F. J., & Pérez-Jiménez, M. J. (2008). A model of the quorum sensing system in Vibrio fischeri using P systems. Artificial Life, 14, 95–109.

    Article  Google Scholar 

  51. Cazzaniga, P., Pescini, D., Besozzi, D., & Mauri, G. (2006). Tau Leaping Stochastic Simulation Method in P Systems. In Hoogeboom, H., Păun, G. H., Rozenberg, G. (eds.) Membrane computing, WMC7, lecture notes in computer science, 4361, 298–313.

  52. Cazzaniga, P., Pescini, D., Romero-Campero, F. J., Besozzi, D., & Mauri, G. (2006). Stochastic approaches in P systems for simulating biological systems. In Gutiérrez-Naranjo, M.A., Păun, Gh., Riscos-Núñez, A., Romero-Campero, F. J. (eds.), Proceedings of the Fourth Brainstorming Week on Membrane Computing, RGNC REPORT 02/2006, Fénix Editora, 145–164.

  53. Pescini, D., Besozzi, D., & Mauri, G. (2005). Investigating local evolutions in dynamical probabilistic P systems. Proceedings of Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC’05), IEEE Computer Press, 440–447.

  54. Pescini, D., Besozzi, D., Mauri, G., & Zandron, C. (2006). Analysis and simulation of dynamics in probabilistic P systems. In: Carbone, A., Pierce, N. (eds) DNA computing, 11th International Workshop on DNA Computing, DNA11, London, ON, Canada, June 6-9, 2005. LNCS 3892, Springer, 236-247.

  55. Pescini, D., Besozzi, D., Mauri, G., & Zandron, C. (2006). Dynamical probabilistic P systems. International Journal of Foundations of Computer Science, 17, 183–204.

    Article  MathSciNet  MATH  Google Scholar 

  56. Sedwards, S., & Mazza, T. (2007). Cyto-Sym: A formal language model and stochastic simulator of membrane-enclosed biochemical processes. Bioinformatics, 23(20), 2800–2802.

    Article  Google Scholar 

  57. Cavaliere, M., & Sedwards, S. (2006). Modelling cellular processes using membrane systems with peripheral and integral proteins. Lecture Notes in Computer Science, 4210, 108–126.

    Article  MathSciNet  Google Scholar 

  58. Nishida, T. Y. (2006). Membrane algorithms. Lecture Notes in Computer Science, 3850, 55–66.

    Article  MATH  Google Scholar 

  59. Nishida, T. Y. (2004). An application of P-system: A new algorithm for NP-complete optimization problems. In: Callaos, N. et al. (eds.) Proceedings of The 8th World Multi-Conference on Systems, Cybernetics and Informatics, V, 109–112.

  60. Nishida, N. Y. (2004). An approximate algorithm for NP-complete optimization problems exploiting P-systems. In: Proceedings of Brainstorming Workshop on Uncertainty in Membrane Computing, Palma de Mallorca, pp. 185–192.

  61. Nishida, N. Y. (2005). Membrane algorithms. Approximate algorithms for NP-complete optimization problems. In G. Ciobanu, Gh Păun, & M. J. Pérez-Jiménez (Eds.), Application of membrane computing (pp. 301–312). Berlin: Springer.

    Google Scholar 

  62. Borrego-Ropero, R., Díaz-Pernil, D., & Pérez-Jiménez, M.J. (2007). Tissue simulator: A graphical tool for tissue P systems. In Vaszil, G. Y. (ed) Proceedings of the International Workshop of Automata for Cellular and Molecular Computing, MTA SZTAKI, Budapest, Hungary, 23–34.

  63. Martín-Vide, C., Păun, Gh, Pazos, J., & Rodríguez-Patón, A. (2003). Tissue P systems. Theoretical Computer Science, 296(2), 295–326.

    Article  MathSciNet  MATH  Google Scholar 

  64. Díaz-Pernil, D., Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2008). A uniform family of tissue P system with cell division solving 3-COL in a linear time. Theoretical Computer Science, 404, 76–87.

    Article  MathSciNet  MATH  Google Scholar 

  65. Ionescu, M., Păun, Gh, & Yokomori, T. (2006). Spiking neural P systems. Fundamenta Informaticae, 71, 279–308.

    MathSciNet  MATH  Google Scholar 

  66. Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., & Ramírez-Martínez, D. (2008). A software tool for verification of spiking neural P systems. Natural Computing, 7, 485–497.

    Article  MathSciNet  MATH  Google Scholar 

  67. Frisco, P., & Gibson, R.T. (2005). A simulator and an evolution program for conformon-P systems. In: TAPS, workshop on theory and applications of P systems, Timişoara, Romania, IEEE Computer Press, 427–430.

  68. Frisco, P., & Ji, S. (2003). Conformons-P systems. Lecture Notes in Computer Science, 2568, 291–301.

    Article  MATH  Google Scholar 

  69. Frisco, P. (2004). The conformon-P system: A molecular and cell biology-inspired computability model. Theoretical Computer Science, 312, 295–319.

    Article  MathSciNet  MATH  Google Scholar 

  70. Corne, D. W., & Frisco, P. (2008). Dynamics of HIV infection studied with cellular automata and conformon-P systems. BioSystems, 91(3), 531–544.

    Article  Google Scholar 

  71. Romero-Jiménez, A., Gutiérrez-Naranjo, M. A., & Pérez-Jiménez, M. J. (2006). Graphical modelling of higher plants using P systems. Lecture Notes in Computer Science, 4361, 496–506.

    Article  Google Scholar 

  72. Romero-Jiménez, A., Gutiérrez-Naranjo, M.A., & Pérez-Jiménez, M.J. (2006). The growth of branching structures with P systems. In Graciani, C. et al. (eds.) Fourth Brainstorming Week on Membrane Computing, Sevilla, Vol. II, Fénix Editora, 253–265.

  73. Rivero-Gil, E., Gutiérrez-Naranjo, M. A., & Pérez-Jiménez, M. J. (2008). Graphics and P systems: Experiments with JPLANT. In: Díaz-Pernil, D., Graciani, C., Gutiérrez-Naranjo, M. A., Păun, G. H., Pérez-Hurtado, I., Riscos-Núñez, A. (eds.) Sixth Brainstorming Week on Membrane Computing, Fénix Editora, Sevilla, 241–254.

  74. Rivero-Gil, E., Gutiérrez-Naranjo, M. A., Pérez-Jiménez, M. J., Romero-Jiménez, A., & Riscos-Núñez, A. (2011). A software tool for generating graphics by means of P systems. Natural computing (Vol. 10, pp. 879–890). New York: Springer.

    MATH  Google Scholar 

  75. Acampora, G., & Loia, V. (2008). A proposal of multi-agent simulation system for membrane computing devices. In: 2007 IEEE Congress on Evolutionary Computation, IEEE XPlore, 4100-4107.

  76. Díaz-Pernil, D., Pérez-Hurtado, I., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2009). A P-Lingua programming environment for membrane computing. Lecture Notes in Computer Science, 5391, 187–203.

    Article  Google Scholar 

  77. García-Quismondo, M., Gutiérrez-Escudero, R., Pérez-Hurtado, I., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2010). An overview of P-Lingua 2.0. Lecture Notes in Computer Science, 5957, 264–288.

    Article  MATH  Google Scholar 

  78. Gershoni, R., Keinan, E., Păun, G., Piran, R., Ratner, T., & Shoshani, S. (2008). Research topics arising from the (planned) P systems. 6th Brainstorming Week on Membrane Computing, Fénix Editora, 183–192.

  79. Keinan, E. (2009). Membrane computing. Google Patents.

  80. Pérez-Hurtado, I., Valencia-Cabrera, L., Pérez-Jiménez, M.J., Colomer, M.A., & Riscos-Núñez, A. (2010). Mecosim: A general purpose software tool for simulating biological phenomena by means of p systems. IEEE Fifth International Conference on Bio-inpired Computing: Theories and Applications (BIC-TA 2010), I 637–643.

  81. Romero-Campero, F. J., Twycross, J., Cámara, M., Bennett, M., Gheorghe, M., & Krasnogor, N. (2009). Modular assembly of cell systems biology models using P systems. International Journal of Foundations of Computer Science, 20(3), 427–442.

    Article  MathSciNet  MATH  Google Scholar 

  82. Colomer, M. A., Margalida, A., Sanuy, D., & Pérez-Jiménez, M. J. (2011). A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study Ecological Modelling (Vol. 222, pp. 33–47). Amsterdam: Elsevier.

    Google Scholar 

  83. Colomer, M. A., Margalida, A., Valencia, L., & Palau, A. (2014). Application of a computational model for complex fluvial ecosystems: The population dynamics of zebra mussel Dreissena polymorpha as a case study. Ecological Complexity, 20, 116–126.

    Article  Google Scholar 

  84. Fondevilla, C., Colomer, M. A., Fillat, F., & Tappeiner, U. (2016). Using a new PDP modelling approach for land-use and land-cover change predictions: A case study in the Stubai Valley (Central Alps). Ecological Modelling, 322, 101–114.

    Article  Google Scholar 

  85. Valencia-Cabrera, L., García-Quismondo, M., Pérez-Jiménez, M.J., Su, Y., Yu, H., & Pan, L. (2013). Modeling Logic Gene Networks by Means of Probabilistic Dynamic P Systems. International Journal of Unconventional Computing, Old City Publishing Inc., 9, 445–464.

  86. Lefticaru, R., Ipate, F., Valencia-Cabrera, L., Turcanu, A., Tudose, C., Gheorghe, M., Pérez-Jiménez, M.J., Niculescu, I.M., & Dragomir, C. (2012). Towards an integrated approach for model simulation, property extraction and verification of P systems. Proceedings of 10th Brainstorming Week on Membrane Computing, Fénix Editora, I, 291–318.

  87. Gheorghe, M., Ipate, F., Lefticaru, R., Pérez-Jiménez, M. J., Turcanu, A., Valencia-Cabrera, L., et al. (2013). 3-COL problem modelling using simple Kernel P systems. International Journal of Computer Mathematics, 90, 816–830. (Taylor & Francis).

    Article  MathSciNet  MATH  Google Scholar 

  88. Colomer, M. A., Margalida, A., & Pérez-Jiménez, M. J. (2013). Population dynamics P system (PDP) Models: A standardized protocol for describing and applying novel bio-inspired computing tools. PLoS One, 8(4), e60698.

    Article  Google Scholar 

  89. Lérida, J. L., Agraz, A., Solsona, F., & Colomer, M. A. (2014). PSysCal: a parallel tool for calibration of ecosystem models. Cluster Computing, 17(2), 271–279.

    Article  Google Scholar 

  90. Blakes, J., Twycross, J., Romero-Campero, F. J., & Krasnogor, N. (2011). The infobiotics workbench: An integrated in silico modelling platform for systems and synthetic biology. Bioinformatics, Oxford, 27(23), 3323–3324.

    Article  Google Scholar 

  91. Buiu, C., Arsene, O., Cipu, C., & Patrascu, M. (2011). A software tool for modeling and simulation of numerical P systems. BioSystems, 103, 442–447.

    Article  Google Scholar 

  92. Arsene, O., Buiu, C., & Popescu, N. (2011). SNUPS—A simulator for numerical membrane computing. International Journal of Innovative Computing, Information and Control, 7, 3509–3522.

    Google Scholar 

  93. Pavel, A. B., Vasile, C. I., & Dumitrache, I. (2012). Robot localization implemented with enzymatic numerical P systems. In: Prescott, T. J., Lepora, N. F., Mura, A., Verschure, P. F. M. J. (Ed.) Biomimetic and biohybrid systems: Proceedings of the first international conference, Living Machines, Barcelona, 204–215.

  94. García-Quismondo, M., Macías-Ramos, L. F., & Pérez-Jiménez, M. J. (2013). Implementing Enzymatic Numerical P Systems for AI Applications by means of Graphic Processing Units. Beyond Artificial Intelligence: Contemplations, Expectations, Applications, Springer Verlag, 4, 137–157.

    Article  Google Scholar 

  95. García-Quismondo, M., Martínez-del-Amor, M.A., & Pérez-Jiménez, M.J. (2014). Probabilistic Guarded P Systems, A New Formal Modelling Framework. In: Gheorghe, M., Rozenberg, G., Salomaa, A., Sosík, P., Zandron, C. (Eds.) Membrane Computing. CMC 2014. Lecture Notes in Computer Science, 8961, 194–214.

  96. García-Quismondo, M., Reed, J. M., Chew, F. S., Martínez-del-Amor, M. A., & Pérez-Jiménez, M. J. (2017). Evolutionary response of a native butterfly to concurrent plant invasions: Simulation of population dynamics. Ecological Modelling, 360, 410–424.

    Article  Google Scholar 

  97. García-Quismondo, M., Levin, M., & Lobo, D. (2017). Modeling regenerative processes with membrane computing. Information Sciences, 381, 229–249.

    Article  Google Scholar 

  98. Campos, M., Llorens, C., Sempere, J. M., Futami, R., Rodriguez, I., Carrasco, P., et al. (2015). A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biology Direct, 10(1), 41.

    Article  Google Scholar 

  99. Shaalan, B., & Muniyandi, R. C. (2015). Implementing mitogen activated protein kinases cascade on membrane computing using P-lingua. Journal of Computer Science, 11(1), 178–187.

    Article  Google Scholar 

  100. Li, J., Huang, Y., & Xu, J. (2016). Decoder design based on spiking neural P systems. IEEE Transactions on NanoBioscience, 15(7), 639–644.

    Article  Google Scholar 

  101. Huang, Y., Li, J., & Xu, J. (2016). Microfluidic Half Adder Chip Based on Spiking Neural P Systems Technical Journal of the Faculty of Engineering. Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia, 39(9), 317–323.

  102. Liu, X., & Xue, J. (2017). A cluster splitting technique by Hopfield networks and P systems on simplices. Neural Processing Letters, 46(1), 171–194.

    Article  Google Scholar 

  103. Giannakis, K., & Andronikos, T. (2017). Membrane automata for modeling biomolecular processes. Natural Computing, 16(1), 151–163.

    Article  MathSciNet  MATH  Google Scholar 

  104. Lefticaru R., Macías-Ramos L.F., Niculescu I.M., & Mierlă, L. (2017). Agent-Based Simulation of Kernel P Systems with Division Rules Using FLAME. In: Leporati A., Rozenberg G., Salomaa A., Zandron C. (eds) Membrane Computing. CMC 2016. Lecture Notes in Computer Science, Springer, 10105, 286–306.

  105. Gheorge, M., Ipate, F., Mierla, L., & Konur, S. (2015). Stochastic approaches in P systems for simulating biological systems. Proceedings of the Thirteenth Brainstorming Week on Membrane Computing, Fénix Editora, 179–194.

  106. Cecilia, J. M., García, J. M., Guerrero, G. D., Martínez-del Amor, M. A., Pérez-Hurtado, I., & Pérez-Jiménez, M. J. (2010). Simulating a P system based efficient solution to SAT by using GPUs. Journal of Logic and Algebraic Programming., 79(6), 317–325.

    Article  MathSciNet  MATH  Google Scholar 

  107. Cecilia, J. M., García, J. M., Guerrero, G. D., Martínez-del Amor, M. A., Pérez-Hurtado, I., & Pérez-Jiménez, M. J. (2010). Simulation of P systems with active membranes on CUDA. Briefings in Bioinformatics, 11(3), 313–322.

    Article  Google Scholar 

  108. Cabarle, F.G.C., Adorna, H., & Martínez-del-Amor, M.A. (2011). An improved GPU simulator for spiking neural P systems. In: Sixth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 262–267.

  109. Cabarle, F.G.C., Adorna, H., & Martínez-del-Amor, M.A. (2012). A spiking neural P system simulator based on CUDA. In: Gheorghe, M., Păun, G., Rozenberg, G., Salomaa, A., Verlan, S. (eds.), CMC 2011, Lecture Notes in Computer Science, 7184, 87–103.

  110. Martínez-del-Amor, M. A., Karlin, I., Jensen, R. E., Pérez-Jiménez, M. J., & Elster, A. C. (2012). Parallel simulation of probabilistic P systems on multicore platforms. Proceedings of the Tenth Brainstorming Week on Membrane Computing, II, 17–26.

    Google Scholar 

  111. Bangalan, Z. F., Soriano, K. A. N., Juayong, R. A. B., Cabarle, F. G. C., Adorna, H. N., & Martínez-del-Amor, M. A. (2013). A GPU Simulation for Evolution-Communication P Systems with Energy Having no Antiport Rules. Proceedings of the Eleventh Brainstorming Week on Membrane Computing, 25–50.

  112. Maroosi, A., & Muniyandi, R.C. (2013). Accelerated simulation of membrane computing to solve the N-queens problem on multi-core. In: Panigrahi B.K., Suganthan P.N., Das S., Dash S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, Springer, 8298.

  113. Maroosi, A., Muniyandi, R. C., Sundararajan, E. A., & Zin, A. M. (2013). Improved implementation of simulation for membrane computing on the graphic processing unit. Procedia Technology, 11, 184–190.

    Article  Google Scholar 

  114. Martínez-del-Amor, M.A., Carrasco, J.P., & Pérez-Jiménez, M.J. (2013). Simulating a Family of Tissue P Systems Solving SAT on the GPU, Eleventh Brainstorming Week on Membrane Computing (11BWMC), Fénix Editora, 201–220.

  115. Martínez-del-Amor, M.A., Macías-Ramos, L.F., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez, M.J. (2014). Accelerated simulation of P systems on the GPU: a survey. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds.) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, Springer, 472, 308–312.

  116. Cabarle, F., Adorna, H., & Martinez-del-Amor, M.A. (2014). Simulating Spiking Neural P systems without delays using GPUs. In Nunes de Castro, L. (Ed.)Natural Computing for Simulation and Knowledge Discovery, IGI Global, 109–121.

  117. Carandang, J. P. A., Villaflores, J. M. B., Cabarle, F. G. C., Adorna, H. N., & Martínez-del-Amor, M. A. (2017). CuSNP: Spiking Neural P Systems Simulators in CUDA. Romanian Journal of Information Science and Technology, 20(1), 57–70.

    Google Scholar 

  118. Martínez-del Amor, M. A., Pérez-Hurtado, I., Pérez-Jiménez, M. J., & Riscos-Núñez, A. (2010). A P-lingua based simulator for tissue P systems. The Journal of Logic and Algebraic Programming, 79(6), 374–382.

    Article  MathSciNet  MATH  Google Scholar 

  119. Macías–Ramos, L.F., Pérez–Hurtado, I., García–Quismondo, M., Valencia–Cabrera, L., Pérez–Jiménez, M.J., & Riscos–Núñez, A. (2012). A P–lingua based simulator for spiking neural P systems. In: Gheorghe, M., Păun, G., Rozenberg, G., Salomaa, A., Verlan, S. (eds.) CMC 2011, Lecture Notes on Computer Science, Springer, 7184, 257–281.

  120. Perez-Hurtado, I., Valencia-Cabrera, L., Chacon, J. M., Riscos-Núñez, A., & Perez-Jimenez, M. J. (2014). A P-lingua based simulator for tissue P systems with cell separation. Romanian Journal of Information Science and Technology, 17(1), 89–102.

    Google Scholar 

  121. Macías-Ramos, L. F., Valencia-Cabrera, L., Song, B., Song, T., Pan, L., & Pérez-Jiménez, M. J. (2015). A P-lingua based simulator for P systems with symport/antiport rules. Fundamenta Informaticae, 139(2), 211–227.

    Article  MathSciNet  MATH  Google Scholar 

  122. Valencia-Cabrera, L., Wu, T., Zhang, Z., Pan, L., & Pérez-Jiménez, M. J. (2017). A simulation software tool for cell-like spiking neural P systems. Romanian Journal of Information Science and Technology, 20(1), 71–84.

    Google Scholar 

  123. Florea, A. G., & Buiu, C. (2016). Development of a software simulator for P colonies - Applications in robotics. International Journal on Unconventional Computing, 12(2–3), 189–205.

    Google Scholar 

  124. Florea, A.G., & Buiu, C. (2017). Synchronized dispersion of robotic swarms using XP colonies. Proceedings of the 8th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2016, 2017, 1–6.

  125. Florea, A.G., & Buiu, C. (2017). Modelling multi-robot interactions using a generic controller based on numerical P systems and ROS. IEEE Proceedings of 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), June 29 - July 01, 1, 1–6.

  126. Florea, A. G., & Buiu, C. (2018). A distributed approach to the control of multi-robot systems using XP colonies. Integrated Computer-Aided Engineering, 25(1), 15–29.

    Article  Google Scholar 

  127. Florea, A. G., & Buiu, C. (2018). A symbolic membrane computing approach to the control of multi-robot systems. Bulletin of the International Membrane Computing Society, 5, 27–30.

    Google Scholar 

  128. Florea, A. G., & Buiu, C. (2018). PeP, an open-source enzymatic numerical P systems simulator. Bulletin of the International Membrane Computing Society, 5, 31.

    Google Scholar 

  129. Pan, L., Song, B., Valencia-Cabrera, L., & Pérez-Jiménez, M. J. (2018). The computational complexity of tissue P systems with evolutional symport/antiport rules. Complexity, 3745210, 21. https://doi.org/10.1155/2018/3745210.

    Article  MATH  Google Scholar 

  130. Qi F., & Liu M. (2017). Optimization Spiking Neural P System for Solving TSP. In: Gu X., Liu G., Li B. (eds) Machine Learning and Intelligent Communications, MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer, 227, 668–676.

  131. Andreu-Guzmán, J. A., & Valencia-Cabrera, L. (2018). Towards a general framework for membrane algorithms. Bulletin of the International Membrane Computing Society, 5, 91–96.

    Google Scholar 

  132. Orellana-Martín, D., Valencia-Cabrera, L., Guisado, J. L., Jiménez-Morales, F., & Pérez-Jiménez, M. J. (2018). Laser dynamics from a membrane computing perspective. Bulletin of the International Membrane Computing Society, 5, 97–108.

    Google Scholar 

  133. Pérez-Hurtado, I., Pérez-Jiménez, M.J., Zhang, G., & Orellana-Martín, D. (2018). Robot Path Planning using Rapidly-exploring Random Trees: A Membrane Computing Approach. IEEE Proceedings of 2018 7th International Conference on Computers Communications and Control, May 8 - 12, Oradea, Romania.

Web links

  1. P systems web page (Ppage). http://ppage.psystems.eu. Accessed July 2019.

  2. P systems Software (in Ppage). http://ppage.psystems.eu/Software. Accessed July 2019.

  3. P systems simulation timeline. https://www.gcn.us.es/SimulationMC. Accessed July 2019.

  4. Research Group on Natural Computing - University of Seville: http://www.gcn.us.es. Accessed July 2019.

  5. Center for BioMedical Computing - Verona: http://www.cbmc.it/. Accessed Aug 2018.

  6. Meta PLab site: http://mplab.scienze.univr.it/index.html. Accessed Nov 2017.

  7. P System Modelling Framework at the University of Sheffield: http://staffwww.dcs.shef.ac.uk/people/M.Gheorghe/PSimulatorWeb/P_Systems_applications.htm. Accessed Sept 2017.

  8. Natural Computing Group - Polytechnic University of Madrid: http://www.gcn.upm.es/. Accessed July 2019.

  9. Cyto-sim site: https://sites.google.com/site/cytosim/home. Accessed July 2019.

  10. The Xholon Project: http://www.primordion.com/Xholon. Accessed July 2019.

  11. P-Lingua website. http://www.p-lingua.org/. Accessed July 2019.

  12. MeCoSim website. http://www.p-lingua.org/mecosim/. Accessed July 2019.

  13. Infobiotics website. http://infobiotics.org/ Accessed July 2019.

  14. MeCoGUI website. http://www.p-lingua.org/wiki/index.php/MeCoGUI. Accessed July 2019.

  15. García-Quismondo, M. A Java-Based P-Lingua Simulator for Enzymatic Numerical P Systems http://www.cs.us.es/blogs/mgarcia/research/software_tools/java_simulator_enps/. Accessed July 2019.

  16. Pieris oleracea model website. http://www.p-lingua.org/wiki/index.php/PGSP_systems:_Pieris_oleracea. Accessed July 2019.

  17. kPWorkbench website. http://kpworkbench.org/. Accessed July 2019.

  18. PMCGPU project. http://www.p-lingua.org/wiki/index.php/PMCGPU. Accessed July 2019.

  19. Florea, A.G., & Buiu, C. (2015). Lulu - a software simulator for P colonies. Use case scenarios and demonstration videos. Zenodo. https://doi.org/10.5281/zenodo.34350.

    Article  Google Scholar 

  20. Florea, A.G., & Buiu, C. (2016). Lulu - an open-source software simulator of P colonies and P swarms. https://github.com/andrei91ro/lulu_pcol_sim. Accessed July 2019.

  21. Pep simulator - GitHub project. https://github.com/andrei91ro/pep. Accessed July 2019.

  22. Timeline in single webpage. http://www.cs.us.es/~lvalencia/SimulationMC.html. Accessed July 2019.

Download references

Acknowledgements

The work of L. Valencia-Cabrera, D. Orellana-Martín, and M.A. Martínez-del-Amor y M.J. Pérez-Jiménez was supported by Project TIN2017-89842-P of the Ministerio de Economía y Competitividad of Spain.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Luis Valencia-Cabrera.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Valencia-Cabrera, L., Orellana-Martín, D., Martínez-del-Amor, M.Á. et al. An interactive timeline of simulators in membrane computing. J Membr Comput 1, 209–222 (2019). https://doi.org/10.1007/s41965-019-00016-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41965-019-00016-z

Keywords

Navigation