Process Calculi Abstractions for Biology

Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-

A framework for protein and membrane interactions

We introduce the BioBeta Framework, a meta-model for both protein-level and membrane-level interactions of living cells. This formalism aims to provide a formal setting where to encode, compare and merge models at different abstraction levels; in particular, higher-level (e.g. membrane) activities can be given a formal biological justification in terms of low-level (i.e., protein) interactions. A BioBeta specification provides a protein signature together a set of protein reactions, in the spirit of the kappa-calculus. Moreover, the specification describes when a protein configuration triggers one of the only two membrane interaction allowed, that is "pinch" and "fuse". In this paper we define the syntax and semantics of BioBeta, analyse its properties, give it an interpretation as biobigraphical reactive systems, and discuss its expressivity by comparing with kappa-calculus and modelling significant examples. Notably, BioBeta has been designed after a bigraphical metamodel for the same purposes. Hence, each instance of the calculus corresponds to a bigraphical reactive system, and vice versa (almost). Therefore, we can inherith the rich theory of bigraphs, such as the automatic construction of labelled transition systems and behavioural congruences

Integrating heterogeneous knowledges for understanding biological behaviors: a probabilistic approach

Despite recent molecular technique improvements, biological knowledge remains incomplete. Reasoning on living systems hence implies to integrate heterogeneous and partial informations. Although current investigations successfully focus on qualitative behaviors of macromolecular networks, others approaches show partial quantitative informations like protein concentration variations over times. We consider that both informations, qualitative and quantitative, have to be combined into a modeling method to provide a better understanding of the biological system. We propose here such a method using a probabilistic-like approach. After its exhaustive description, we illustrate its advantages by modeling the carbon starvation response in Escherichia coli. In this purpose, we build an original qualitative model based on available observations. After the formal verification of its qualitative properties, the probabilistic model shows quantitative results corresponding to biological expectations which confirm the interest of our probabilistic approach.Comment: 10 page

Nature as a Network of Morphological Infocomputational Processes for Cognitive Agents

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted

Minimizing Reaction Systems

The theoretical model for reaction systems is a relatively new framework originally proposed as a mathematical model for biochemical processes which take place in living cells. Growing interest in this research area has lead to the abstraction of the model for non-biological purpose as well. Reaction systems, with a well understood behavior, have become important for studying transition systems. As with any mathematical model, we want to simplify a given implementation of the model as much as possible while maintaining functional equivalence. This paper discusses the formal model for reaction systems, how we can simplify them with minimization techniques, some of their capabilities and properties, and a comparison of those properties for minimal and non-minimal reaction systems. Original software written for the purpose of exploring reaction systems for this paper as well as well-known logic minimization algorithms instrumental in simplifying reaction systems are discussed

Some resonances between Eastern thought and Integral Biomathics in the framework of the WLIMES formalism for modelling living systems

Forty-two years ago, Capra published “The Tao of Physics” (Capra, 1975). In this book (page 17) he writes: “The exploration of the atomic and subatomic world in the twentieth century has …. necessitated a radical revision of many of our basic concepts” and that, unlike ‘classical’ physics, the sub-atomic and quantum “modern physics” shows resonances with Eastern thoughts and “leads us to a view of the world which is very similar to the views held by mystics of all ages and traditions.“ This article stresses an analogous situation in biology with respect to a new theoretical approach for studying living systems, Integral Biomathics (IB), which also exhibits some resonances with Eastern thought. Stepping on earlier research in cybernetics1 and theoretical biology,2 IB has been developed since 2011 by over 100 scientists from a number of disciplines who have been exploring a substantial set of theoretical frameworks. From that effort, the need for a robust core model utilizing advanced mathematics and computation adequate for understanding the behavior of organisms as dynamic wholes was identified. At this end, the authors of this article have proposed WLIMES (Ehresmann and Simeonov, 2012), a formal theory for modeling living systems integrating both the Memory Evolutive Systems (Ehresmann and Vanbremeersch, 2007) and the Wandering Logic Intelligence (Simeonov, 2002b). Its principles will be recalled here with respect to their resonances to Eastern thought

Systems modelling and the development of coherent understanding of cell biology

This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education, introducing systems modelling as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general 2-D model of cells, a 3-D model of plant cells and finally they are engaged in formal thinking by modelling life phenomena to a hierarchical systems model. The strategy was thought out, elaborated and tested in classrooms in several research cycles. Throughout the field-tests, research data were collected by means of classroom observations, interviews, audio-taped discussions, completed worksheets, written tests and questionnaires. Reflection on the research findings eventuated in reshaping and formalizing the learning and teaching strategy, which is presented here. The results show that although acquiring systems thinking competence at the metacognitive level needs more effort, our strategy contributed to improving learning outcomes, i.e. acquisition of a coherent conceptual understanding of cell biology and acquisition of initial systems thinking competence, with modelling being the key activity

A Note on P Systems with Activators

The usual assumption in P systems behavior is that of maximal parallelism, however in living cells it is not the case because they have a limited number of enzymes. The aim of this paper is to try to merge these ideas by introducing a notion of activator - a formal model of enzyme as a usual symbol- object, more or less a middle notion between a catalyst and a promoter. Each activator executes one (context-free) rule, and can evolve in the same step. The rules will need activators to be applied, so the parallelism of each rule is maximal, but limited to the number of its activators. Such systems can generate any recursively enumerable language or determinis- tically accept any recursively enumerable set of vectors of nonnegative integers. It is open what is the power of P systems with uniport rules and activator

Modelling gene expression control using P systems: The Lac Operon, a case study

In this paper P systems are used as a formal framework for the specification and simulation of biological systems. In particular, we will deal with gene regulation systems consisting of protein–protein and protein–DNA interactions that take place in different compartments of the hierarchical structure of the living cell or in different individual cells from a colony. We will explicitly model transcription and translation as concurrent and discrete processes using rewriting rules on multisets of objects and strings. Our approach takes into account the discrete character of the components of the system, its random behaviour and the key role played by membranes in processes involving signalling at the cell surface and selective uptake of substances from the environment. Our systems will evolve according to an extension of Gillespie’s algorithm, called Multicompartmental Gillespie’s Algorithm. The well known gene regulation system in the Lac Operon in Escherichia coli will be modelled as a case study to benchmark our approach.Ministerio de Ciencia y Tecnología TIN2005-09345-C04-0