Enhancing P Systems for Complex Biological Simulations

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.