A uniform framework for modeling based on P Systems

In this paper, a P systems based general framework for modeling the dynamics of a population biology is presented. Multienvironment probabilistic functional P systems with active membranes provide the syntactical specification, and the semantics is captured by using stochastic or probabilistic strategies implemented through simulation algorithms.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08–TIC-0420

A Model of Antibiotic Resistance Evolution Dynamics Through P Systems with Active Membranes and Communication Rules

Baquero, F.; Campos Frances, M.; Llorens, C.; Sempere Luna, JM. (2018). A Model of Antibiotic Resistance Evolution Dynamics Through P Systems with Active Membranes and Communication Rules. Lecture Notes in Computer Science. 11270:33-44. https://doi.org/10.1007/978-3-030-00265-7_3S334411270Barbacari, N., Profir, A., Zelinschi, C.: Gene regulatory network modeling by means of membrane computing. In: Proceedings of the 7th International Workshop on Membrane Computing WMC 2006. LNCS, vol. 4361, pp. 162–178 (2006)Besozzi, D., Cazzaniga, P., Cocolo, S., Mauri, G., Pescini, D.: Modeling diffusion in a signal transduction pathway: the use of virtual volumes in P systems. Int. J. Found. Comput. Sci. 22(1), 89–96 (2011)Campos, M.: A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biol. Direct 10(1), 41 (2015)Ciobanu, G., Păun, Gh., Pérez-Jiménez, M.J.: Applications of Membrane Computing. Springer, Heidelberg (2006). https://doi.org/10.1007/3-540-29937-8Colomer, M.A., Margalida, A., Sanuy, D., Pérez-Jiménez, M.J.: A bio-inspired model as a new tool for modeling ecosystems: the avian scavengeras a case study. Ecol. Model. 222(1), 33–47 (2011)Colomer, M.A., Martínez-del-Amor, M.A., Pérez-Hurtado, I., Pérez-Jiménez, M.J., Riscos-Núñez, A.: A uniform framework for modeling based on P systems. In: Li, K., Nagar, A.K., Thamburaj, R. (eds.) IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2010), vol. 1, pp. 616–621 (2010)Dassow, J., Păun, Gh.: On the power of membrane computing. TUCS Technical Report No. 217 (1998)Frisco, P., Gheorghe, M., Pérez-Jiménez, M.J. (eds.): Applications of Membrane Computing in Systems and Synthetic Biology. ECC, vol. 7. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-03191-0Păun, Gh.: Computing with membranes. J. Comput. Syst. Sci. 61(1), 108–143 (2000)Păun, Gh.: Membrane Computing: An Introduction. Springer, Heidelberg (2002). https://doi.org/10.1007/978-3-642-56196-2Păun, Gh., Rozenberg, G., Salomaa, A. (eds.): The Oxford Handbook of Membrane Computing. Oxford University Press, Oxford (2010)World Health Organization: Antimicrobial Resistance: Global Report on Surveillance (2014

A New Strategy to Improve the Performance of PDP-Systems Simulators

One of the major challenges that current P systems simulators have to deal with is to be as efficient as possible. A P system is syntactically described as a membrane structure delimiting regions where multisets of objects evolve by means of evolution rules. According to that, on each computation step, the applicability of the rules for the current P system configuration must be calculated. In this paper we extend previous works that use Rete-based simulation algorithm in order to improve the time consumed during the checking phase in the selection of rules. A new approach is presented, oriented to the acceleration of Population Dynamics P Systems simulations.Ministerio de Economía y Competitividad TIN2012- 3743

Probabilistic Guarded P Systems, A New Formal Modelling Framework

Multienvironment P systems constitute a general, formal framework for modelling the dynamics of population biology, which consists of two main approaches: stochastic and probabilistic. The framework has been successfully used to model biologic systems at both micro (e.g. bacteria colony) and macro (e.g. real ecosystems) levels, respectively. In this paper, we extend the general framework in order to include a new case study related to P. Oleracea species. The extension is made by a new variant within the probabilistic approach, called Probabilistic Guarded P systems (in short, PGP systems). We provide a formal definition, a simulation algorithm to capture the dynamics, and a survey of the associated software.Ministerio de Economía y Competitividad TIN2012- 37434Junta de Andalucía P08-TIC-0420

A View of P Systems from Information Theory

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-54072-6_22In this work we propose new view of P systems by using the framework of Information Theory. Given a cell-like P system with communication and evolution rules, we analyze the amount of information that it holds as the result of symbol movements across the membranes. Under this approach, we propose new definitions and results related to the information of P systems and their entropy. In addition, we propose a new working manner for P systems based only in the entropy evolution during the computation time.Work partially supported by the Spanish Ministry of Economy and Competitiveness under EXPLORA Research Project SAF2013-49788-EXP.Sempere Luna, JM. (2017). A View of P Systems from Information Theory. En International Conference on Membrane Computing. Springer Verlag (Germany). 352-362. https://doi.org/10.1007/978-3-319-54072-6 22S35236