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-

Some Notes on (Mem)Brane Computation

Membrane Computing and Brane Calculi are two recent computational paradigms in the framework of Natural Computing. They are based on the study of the structure and functioning of living cells as living organisms able to process and generate information. In this paper we give a short introduction to both areas and point out some open research lines.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58

Measurable Stochastics for Brane Calculus

We give a stochastic extension of the Brane Calculus, along the lines of recent work by Cardelli and Mardare. In this presentation, the semantics of a Brane process is a measure of the stochastic distribution of possible derivations. To this end, we first introduce a labelled transition system for Brane Calculus, proving its adequacy w.r.t. the usual reduction semantics. Then, brane systems are presented as Markov processes over the measurable space generated by terms up-to syntactic congruence, and where the measures are indexed by the actions of this new LTS. Finally, we provide a SOS presentation of this stochastic semantics, which is compositional and syntax-driven.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Mutual Mobile Membranes Systems with Surface Objects

In this paper we introduce mutual mobile membranes with surface objects, systems which have biological motivation. In P systems with mobile membranes with surface objects, a membrane may enter or exit another membrane. The second membrane just undergoes the action, meaning that it has no control on when the movement takes place. This kind of movement illustrates the lack of an agreement (synchronization) similar to an asynchronous evolution. In mutual mobile membranes with surface objects this aspect is adjusted: any movement takes place only if both participants agree by synchronizing their evolution. In membranes two kinds of competition can occur: resource competition and location competition. Resource competition refers to rules which request the same resources, and the available resources can only be allocated to some of the rules. Location competition refers to the movement of a membrane in the hierarchical structure of the membrane systems under the request of some conflict rules.We use the two variants of membrane systems in order to describe and explain these kinds of competition, and introduce synchronizing objects in mutual mobile membranes which will help to solve the resource and location competitions

A Global Occurrence Counting Analysis for Brane Calculi

We propose a polynomial static analysis for Brane Calculi, based on Abstract Interpretation techniques. The analysis provides a description of the possible hierarchical structure of membranes and of the processes possibly associated to each membrane, together with global occurrence counting information. Our analysis can be applied in the biological setting to investigate systems in which the information on the number of membranes occurring in the system plays a crucial role

Abstract Machines of Systems Biology (Extended Abstract)

Living cells are extremely well-organized autonomous systems, consisting of discrete interacting components. Key to understanding and modelling their behavior is modelling their system organization, which can be described as a collection of distinct but interconnected abstract machines. Biologists have invented a number of notations attempting to describe, abstractly, these abstract machines and the processes that they implement. Systems biology aims to understand how these abstract machines work, separately and together

P Systems with Endosomes

P Systems are computing devices inspired by the structure and the func- tioning of a living cell. A P System consists of a hierarchy of membranes, each of them containing a multiset of objects, a set of evolution rules, and possibly other membranes. Evolution rules are applied to the objects of the same membrane with maximal parallelism. In this paper we present an extension of P Systems, called P Systems with Endosomes (PE Systems), in which endosomes can be explicitly modeled. We show that PE Systems are universal even if only the simplest form of evolution rules is considered, and we give one application examples

A static analysis for Brane Calculi providing global occurrence counting information

In this paper we propose a static analysis for Brane Calculi [1], based on Abstract Interpretation [2] techniques. Our analysis statically approximates the dynamic behaviour of Brane systems, by providing a description of the possible hierarchical structure of membranes and of the processes possibly associated to each membrane, together with global occurrence counting information. Our analysis can be computed in polynomial time. We apply it to investigate several biological systems in which occurrence counting information plays a crucial role. In particular, our case study concerns the formation of the haemoglobin polymer in presence of alterations and investigate the influence that such alterations have on the ability of the haemoglobin polymer to bind oxygen molecules

Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway.

BACKGROUND: Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by "in silico" experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have recently proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format and is, thus, usable for analysis via existing simulation techniques. RESULTS: Here we use a high-level narrative language in designing a computational model of the gp130/JAK/STAT signalling pathway and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then "experiment" on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. CONCLUSION: The described narrative model of the gp130/JAK/STAT pathway represents an interesting case study showing how, by using this approach, researchers can model biological systems without explicitly dealing with formal notations and mathematical expressions (typically used for biochemical modelling), nevertheless being able to obtain simulation and analysis results. We present the model and the sensitivity analysis results we have obtained, that allow us to identify the parameters which are most sensitive to perturbations. The results, which are shown to be in agreement with existing mathematical models of the gp130/JAK/STAT pathway, serve us as a form of validation of the model and of the approach itself