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

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

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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_3

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/124694

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Título: A Model of Antibiotic Resistance Evolution Dynamics Through P Systems with Active Membranes and Communication Rules
Autor: Baquero, Fernando Campos Frances, Marcelino Llorens, Carlos Sempere Luna, José María
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Fecha de fin de embargo: 2019-09-15
Derechos de uso: Reserva de todos los derechos
Fuente:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-00265-7_3
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/978-3-030-00265-7_3
Tipo: Artículo

References

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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) [+]
Barbacari, 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/10.1007/3-540-29937-8

Colomer, 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/10.1007/978-3-319-03191-0

Păun, 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/10.1007/978-3-642-56196-2

Păun, 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)

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