Formal Executable Descriptions of Biological Systems (original) (raw)

Process Calculi Abstractions for Biology

Natural Computing Series, 2009

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 syntaxdriven rules.

Modelling the dynamics of biosystems

Briefings in Bioinformatics, 2004

The need for a more formal handling of biological information processing with stochastic and mobile process algebras is addressed. Biology can benefit this approach, yielding a better understanding of behavioural properties of cells, and computer science can benefit this approach, obtaining new computational models inspired by nature.

Applications of process algebra in systems biology

2006

Abstract This report introduces some of the ongoing work in the application of process algebra in systems biology. This survey reveals that although progress has been made in using process algebra to create stochastic simulations of the systems in question, no work has been done to emphasise the importance of refinement theory. A brief description of the notation and some of the semantics of Communicating Sequential Processes, a process algebra, are presented, with the aim of applying refinement in biological models.

Simulating Biological Systems in the Stochastic Pi-calculus

2004

This course presents a programming language for designing and simulating com- puter models of biological systems. The language is based on a mathematical formalism known as the pi-calculus, and the simulation algorithm is based on standard kinetic theory of physical chemistry. The language will first be presented using a simple graphical notation, and will subsequently be used to model and

A Stochastic Concurrent Constraint Based Framework to Model and Verify Biological Systems

Clei Electronic Journal, 2006

Concurrent process calculi are powerful formalisms for modelling concurrent systems. The mathematical style underlying process calculi allow to both model and verify properties of a system, thus providing a concrete design methodology for complex systems. ntcc , a constraints-based calculus for modeling temporal non-deterministic and asynchronous behaviour of processes has been proposed recently. Process interactions in ntcc can be determined by partial information (i.e. constraints) accumulated in a global store. ntcc has also an associated temporal logic with a proof system that can be conveniently used to formally verify temporal properties of processes. We are interested in using ntcc to model the activity of genes in biological systems. In order to account for issues such as the basal rate of reactions or binding affinities of molecular components, we believe that stochastic features must be added to the calculus. In this paper we propose an extension of ntcc with various stochastic constructs. We describe the syntax and semantics of this extension together with the new temporal logic and proof system associated with it. We show the relevance of the added features by modelling a non trivial biological system: the gene expression mechanisms of the λ virus. We argue that this model is both more elaborate and compact than the stochastic π calculus model proposed recently for the same system.

Stochastic simulation of multiple process calculi for biology

Theoretical Computer Science, 2012

Numerous programming languages based on process calculi have been developed for biological modelling, many of which can generate potentially unbounded numbers of molecular species and reactions. As a result, such languages cannot rely on standard reaction-based simulation methods, and are generally implemented using custom stochastic simulation algorithms. As an alternative, this paper proposes a generic abstract machine that can be instantiated to simulate a range of process calculi using a range of simulation methods. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. We instantiate the generic abstract machine with two Markovian simulation methods and provide encodings for four process calculi: the agent-based pi-calculus, the compartment-based bioambient calculus, the rule-based kappa calculus and the domain-specific DNA strand displacement calculus. We present a generic method for proving that the encoding of an arbitrary process calculus into the abstract machine is correct, and we use this method to prove the correctness of all four calculus encodings. Finally, we demonstrate how the generic abstract machine can be used to simulate heterogeneous models in which discrete communicating sub-models are written using different domain-specific languages and then simulated together. Our approach forms the basis of a multi-language environment for the simulation of heterogeneous biological models.

A Graphical Representation for Biological Processes in the Stochastic pi-Calculus

Lecture Notes in Computer Science, 2006

This paper presents a graphical representation for the stochastic π-calculus, which is formalised by defining a corresponding graphical calculus. The graphical calculus is shown to be reduction equivalent to stochastic π, ensuring that the two calculi have the same expressive power. The graphical representation is used to model a couple of example biological systems, namely a bistable gene network and a mapk signalling cascade. One of the benefits of the representation is its ability to highlight the existence of cycles, which are a key feature of biological systems. Another benefit is its ability to animate interactions between system components, in order to visualise system dynamics. The graphical representation can also be used as a front end to a simulator for the stochastic π-calculus, to help make modelling and simulation of biological systems more accessible to non computer scientists.

An Automated Translation from a Narrative Language for Biological Modelling into Process Algebra

Computational Methods in Systems Biology, 2007

The aim of this work is twofold. First, we propose an high level textual modelling language, which is meant to be biologically intuitive and hence easily usable by life scientists in modelling intra-cellular systems. Secondly, we provide an automatic translation of the proposed language into Beta-binders, a bio-inspired process calculus, which allows life scientists to formally analyse and simulate their

A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems

2007

This paper introduces Protein Calculus, a special modeling language designed for encoding and calculating the behaviors of compartmentilized biological systems. The formalism combines, in a unified framework, two successful computational paradigms -process algebras and membrane systems. The goal of Protein Calculus is to provide a formal tool for transforming collected information from in vivo experiments into coded definition of the different types of proteins, complexes of proteins, and membrane-organized systems of such entities. Using this encoded information as input, our calculus computes, in silico, the possible behaviors of a living system.