Computing with cells: membrane systems - some complexity issues.

Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism

Simulating accepting networks of evolutionary processors with filtered connections by accepting evolutionary P systems

In this work, we propose a variant of P system based on the rewriting of string-objects by means of evolutionary rules. The membrane structure of such a P system seems to be a very natural tool for simulating the filters in accepting networks of evolutionary processors with filtered connections. We discuss an informal construction supporting this simulation. A detailed proof is to be considered in an extended version of this work

A Multiscale Modeling Framework Based on P Systems

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems. The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems. In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems. The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.Kingdom's Engineering and Physical Sciences Research Council EP/ E017215/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/F01855X/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/D019613/

Membrane Computing as a Modelling Tool: Looking Back and Forward from Sevilla

This paper is a tribute to Prof. Mario de Jesús Pérez- Jiménez. An overview of modelling applications in membrane computing has been compiled, trying to narrate it from a historical perspective and including numerous bibliographical references. Since being exhaustive was obviously out of scope, this quick tour on almost two decades of applications is biased, paying special attention to the contributions in which Prof. Pérez-Jiménez and members of his research group were involved.Ministerio de Economía y Competitividad TIN2017-89842-

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

Programmability of Chemical Reaction Networks

Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri Nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior

GENERAL ASPECTS REGARDING THE GROWTH FRESHWATER FISH IN CUBES, AN ALTERNATIVE FOR AQUACULTURE IN ROMANIA

Due to the increased consumption of fish, as an alternative to achieving healthy population nutrition, the development of European aquaculture also shows an increasing trend. At present, freshwater culture is about 42% of total European fish production. Valuable species, from an economic point of view, can be reared in intensive systems in cages on running waters or ponds, combined with less valuable species. There are also new species that are gradually becoming increasingly important for the fish industry in Europe. Freshwater aquaculture in Romania is based on rainbow trout and carp which are still predominant species, but there is significant demand for valuable fish species [11,12,16]. Â

Modelling and validating an engineering application in kernel P systems

© 2018, Springer International Publishing AG. This paper illustrates how kernel P systems (kP systems) can be used for modelling and validating an engineering application, in this case a cruise control system of an electric bike. The validity of the system is demonstrated via formal verification, carried out using the kPWorkbench tool. Furthermore, we show how the kernel P system model can be tested using automata and X-machine based techniques

The Nondeterministic Waiting Time Algorithm: A Review

We present briefly the Nondeterministic Waiting Time algorithm. Our technique for the simulation of biochemical reaction networks has the ability to mimic the Gillespie Algorithm for some networks and solutions to ordinary differential equations for other networks, depending on the rules of the system, the kinetic rates and numbers of molecules. We provide a full description of the algorithm as well as specifics on its implementation. Some results for two well-known models are reported. We have used the algorithm to explore Fas-mediated apoptosis models in cancerous and HIV-1 infected T cells