Enhancing P Systems for Complex Biological Simulations

Elsayed, Aya Allah; Ceprián, Raquel; Hafez, Ahmed Ibrahem; Llorens, Carlos; Sempere, José M.

doi:10.3390/app16020705

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Open AccessArticle

Enhancing P Systems for Complex Biological Simulations

by

Aya Allah Elsayed

^1,2,*,†,

Raquel Ceprián

^1,†,

Ahmed Ibrahem Hafez

^1,†

,

Carlos Llorens

^1,†

and

José M. Sempere

^2,3,*,†

¹

Biotechvana, Parc Científic Universitat de València, 46980 Paterna, Spain

²

Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain

³

Valencian Graduate School and Research Institute of Artificial Intelligence, Camino de Vera s/n, 46022 Valencia, Spain

^*

Authors to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

Appl. Sci. 2026, 16(2), 705; https://doi.org/10.3390/app16020705

Submission received: 17 October 2025 / Revised: 18 December 2025 / Accepted: 26 December 2025 / Published: 9 January 2026

(This article belongs to the Section Computing and Artificial Intelligence)

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Abstract

Membrane computing, and more specifically P systems, has been a useful tool in the simulation of biological systems, both at the biomolecular and cellular levels, and also in microbial and ecological communities. The need for greater realism in the simulations of these systems has been growing in the recent years. Thus, it has become clear that the rules, objects and structures of P systems cannot always be useful to model some aspects of biological systems. Specifically, some aspects of population dynamics were not perfectly reflected in the P systems that supported these models. In this work we propose new types of rules that help to model some aspects of biological systems in a more realistic way. Fundamentally, our proposal focuses on the use of probabilistic parameters that help create probabilistic and stochastic models for biological systems. In addition, given the high complexity of some of these systems, in this work we describe two software tools that we have developed and that help in the validation and debugging of these systems.

Keywords: membrane computing; P system rules; systems biology

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MDPI and ACS Style

Elsayed, A.A.; Ceprián, R.; Hafez, A.I.; Llorens, C.; Sempere, J.M. Enhancing P Systems for Complex Biological Simulations. Appl. Sci. 2026, 16, 705. https://doi.org/10.3390/app16020705

AMA Style

Elsayed AA, Ceprián R, Hafez AI, Llorens C, Sempere JM. Enhancing P Systems for Complex Biological Simulations. Applied Sciences. 2026; 16(2):705. https://doi.org/10.3390/app16020705

Chicago/Turabian Style

Elsayed, Aya Allah, Raquel Ceprián, Ahmed Ibrahem Hafez, Carlos Llorens, and José M. Sempere. 2026. "Enhancing P Systems for Complex Biological Simulations" Applied Sciences 16, no. 2: 705. https://doi.org/10.3390/app16020705

APA Style

Elsayed, A. A., Ceprián, R., Hafez, A. I., Llorens, C., & Sempere, J. M. (2026). Enhancing P Systems for Complex Biological Simulations. Applied Sciences, 16(2), 705. https://doi.org/10.3390/app16020705

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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