This document is structured in three parts, whose content is briefly outlined below. Part I: Preliminaries Chapter I familiarizes the reader with the basics of Natural Computing, introducing some classical models in the discipline. Following, it delves into the state of the art of Membrane Computing. Some frameworks including the seminar transition model are discussed. Finally, it contra sts stochastic and probabilistic approaching when modelling real-life phenomena. Chapter II discusses simulators in Membrane Computing and describes the project P-Lingua and the software tool pLinguaCore, which enable experts to describe and simulate P systems automatically. Moreover, some Membrane Computing simulators implemented on parallel platforms are described, with an special emphasis on those developed for Graphic Processing Units (GPU). Part II: Contributions Chapter III discusses Enzymatic Numerical P Systems (ENPS), a deterministic model for robotics, introducing its antecedents and sequential simulators. In addition, a parallel, GPU-based simulator is presented, including a performance analysis with some case studies and a methodology for repeated simulation of ENPSs. Chapter IV discusses a model on Logic Networks (LNs), which are a specific type of Gene Regulatory Networks in which the combination of the states of a set of genes can influence another one. In addition, a model based on Population Dynamic P systems (PDP systems, for short) is finally presented, describing its semantics and its elements in detail. Chapter V formalizes Probabilistic Guarded P Systems (PGP Systems, for short), a new modelling framework for ecology. The characteristic features of this approach are described, i.e., its spatial distribution and elements and its syntax and semantics. A parallel, GPU-based simulator is described, as well as the integration of PGP systems into the P-Lingua framework. Part III: Results Chapter VI presents some case studies on the models and simulators described in part II, specifically, the modelling and simulation of a Logic Network involved in the flowering process of Arabidopsis thaliana by means of LNDP systems and the modelling and simulation of the ecosystem of White Cabbage Buttery (Pieris napi oleracea). Chapter VII focuses on the results compiled in this document, recapitulating the achievements and conclusions of this thesis and discussing some new lines of work resulting from it.