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BioPEPA: a framework for the modelling and analysis of biological systems
, 2008
"... In this work we present BioPEPA, a process algebra for the modelling and the analysis of biochemical networks. It is a modification of PEPA, originally defined for the performance analysis of computer systems, in order to handle some features of biological models, such as stoichiometry and the use ..."
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Cited by 94 (25 self)
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In this work we present BioPEPA, a process algebra for the modelling and the analysis of biochemical networks. It is a modification of PEPA, originally defined for the performance analysis of computer systems, in order to handle some features of biological models, such as stoichiometry and the use of general kinetic laws. The domain of application is the one of biochemical networks. BioPEPA may be seen as an intermediate, formal, compositional representation of biological systems, on which different kinds of analysis can be carried out. BioPEPA is enriched with some notions of equivalence. Specifically, the isomorphism and strong bisimulation for PEPA have been considered. Finally, we show the translation of three biological models into the new language and we report some analysis results.
Scalable simulation of cellular signaling networks
 IN PROCEEDINGS OF APLAS 2007
, 2007
"... Given the combinatorial nature of cellular signalling pathways, where biological agents can bind and modify each other in a large number of ways, concurrent or agentbased languages seem particularly suitable for their representation and simulation [1–4]. Graphical modelling languages such as κ [5– ..."
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Cited by 59 (13 self)
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Given the combinatorial nature of cellular signalling pathways, where biological agents can bind and modify each other in a large number of ways, concurrent or agentbased languages seem particularly suitable for their representation and simulation [1–4]. Graphical modelling languages such as κ [5–8], or the closely related BNG language [9– 14], seem to afford particular ease of expression. It is unclear however how such models can be implemented. 6 Even a simple model of the EGF receptor signalling network can generate more than 10 23 nonisomorphic species [5], and therefore no approach to simulation based on enumerating species (beforehand, or even onthefly) can handle such models without sampling down the number of potential generated species. We present in this paper a radically different method which does not attempt to count species. The proposed algorothm uses a representation of the system together with a superapproximation of its ‘event horizon ’ (all events that may happen next), and a specific correction scheme to obtain exact timings. Being completely local and not based on any kind of enumeration, this algorithm has a per event time cost which is independent of (i) the size of the set of generable species (which can even be infinite), and (ii) independent of the size of the system (ie, the number of agent instances). We show how to refine this algorithm, using concepts derived from the classical notion of causality, so that in addition to the above one also has that the even cost is depending (iii) only logarithmically on the size of the model (ie, the number of rules). Such complexity properties reflect in our implementation which, on a current computer, generates about 10 6 events per minute in the case of the simple EGF receptor model mentioned above, using a system with 10 5 agents.
A Programming Language for Composable DNA Circuits
 J. R. SOC INTERFACE
, 2009
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Rulebased modeling of biochemical systems with BioNetGen
 IN METHODS IN MOLECULAR BIOLOGY: SYSTEMS BIOLOGY
, 2009
"... Rulebased modeling involves the representation of molecules as structured objects and molecular interactions as rules for transforming the attributes of these objects. The approach is notable in that it allows one to systematically incorporate sitespecific details about proteinprotein interactio ..."
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Cited by 43 (10 self)
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Rulebased modeling involves the representation of molecules as structured objects and molecular interactions as rules for transforming the attributes of these objects. The approach is notable in that it allows one to systematically incorporate sitespecific details about proteinprotein interactions into a model for the dynamics of a signaltransduction system, but the method has other applications as well, such as following the fates of individual carbon atoms in metabolic reactions. The consequences of proteinprotein interactions are difficult to specify and track with a conventional modeling approach because of the large number of protein phosphoforms and protein complexes that these interactions potentially generate. Here, we focus on how a rulebased model is specified in the BioNetGen language (BNGL) and how a model specification is analyzed using the BioNetGen software tool. We also discuss new developments in rulebased modeling that should enable the construction and analyses of comprehensive models for signal transduction pathways and similarly largescale models for other biochemical systems.
Abstract interpretation of cellular signalling networks
 4905 OF LNCS
, 2008
"... Cellular signalling pathways, where proteins can form complexes and undergo a large array of post translational modifications are highly combinatorial systems sending and receiving extracellular signals and triggering appropriate responses. Processcentric languages seem apt to their representatio ..."
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Cited by 33 (8 self)
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Cellular signalling pathways, where proteins can form complexes and undergo a large array of post translational modifications are highly combinatorial systems sending and receiving extracellular signals and triggering appropriate responses. Processcentric languages seem apt to their representation and simulation [1–3]. Rulecentric languages such as κ [4–8] and BNG [9, 10] bring in additional ease of expression. We propose in this paper a method to enumerate a superset of the reachable complexes that a κ rule set can generate. This is done via the construction of a finite abstract interpretation. We find a simple criterion for this superset to be the exact set of reachable complexes, namely that the superset is closed under swap, an operation whereby pairs of edges of the same type can permute their ends. We also show that a simple syntactic restriction on rules is sufficient to ensure the generation of a swapclosed set of complexes. We conclude by showing that a substantial rule set (presented in Ref. [4]) modelling the EGF receptor pathway verifies that syntactic condition (up to suitable transformations), and therefore despite its apparent complexity has a rather simple set of reachables.
Statistical model checking in BioLab: applications to the automated analysis of TCell receptor signaling pathway
 In CMSB’08
, 2008
"... Abstract. We present an algorithm, called BioLab, for verifying temporal properties of rulebased models of cellular signalling networks. BioLab models are encoded in the BioNetGen language, and properties are expressed as formulae in probabilistic bounded linear temporal logic. Temporal logic is a ..."
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Cited by 25 (7 self)
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Abstract. We present an algorithm, called BioLab, for verifying temporal properties of rulebased models of cellular signalling networks. BioLab models are encoded in the BioNetGen language, and properties are expressed as formulae in probabilistic bounded linear temporal logic. Temporal logic is a formalism for representing and reasoning about propositions qualified in terms of time. Properties are then verified using sequential hypothesis testing on executions generated using stochastic simulation. BioLab is optimal, in the sense that it generates the minimum number of executions necessary to verify the given property. BioLab also provides guarantees on the probability of it generating TypeI (i.e., falsepositive) and TypeII (i.e., falsenegative) errors. Moreover, these error bounds are prespecified by the user. We demonstrate BioLab by verifying stochastic effects and bistability in the dynamics of the Tcell receptor signaling network.
Abstracting the differential semantics of rulebased models: exact and automated model reduction (revised version)
, 2010
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Rulebased modelling, symmetries, refinements
"... Abstract. Rulebased modelling is particularly effective for handling the highly combinatorial aspects of cellular signalling. The dynamics is described in terms of interactions between partial complexes, and the ability to write rules with such partial complexesi.e., not to have to specify all the ..."
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Cited by 20 (9 self)
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Abstract. Rulebased modelling is particularly effective for handling the highly combinatorial aspects of cellular signalling. The dynamics is described in terms of interactions between partial complexes, and the ability to write rules with such partial complexesi.e., not to have to specify all the traits of the entitities partaking in a reaction but just those that matter is the key to obtaining compact descriptions of what otherwise could be nearly infinite dimensional dynamical systems. This also makes these descriptions easier to read, write and modify. In the course of modelling a particular signalling system it will often happen that more traits matter in a given interaction than previously thought, and one will need to strengthen the conditions under which that interaction may happen. This is a process that we call rule refinement and which we set out in this paper to study. Specifically we present a method to refine rule sets in a way that preserves the implied stochastic semantics.
Efficient Turinguniversal computation with DNA polymers (extended abstract)
"... Abstract. Bennett’s proposed chemical Turing machine is one of the most important thought experiments in the study of the thermodynamics of computation. Yet the sophistication of molecular engineering required to physically construct Bennett’s hypothetical polymer substrate and enzyme has deterred e ..."
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Cited by 20 (4 self)
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Abstract. Bennett’s proposed chemical Turing machine is one of the most important thought experiments in the study of the thermodynamics of computation. Yet the sophistication of molecular engineering required to physically construct Bennett’s hypothetical polymer substrate and enzyme has deterred experimental implementations. Here we propose a chemical implementation of stack machines — a Turinguniversal model of computation similar to Turing machines — using strand displacement cascades as the underlying chemical primitive. More specifically, the mechanism described herein is the addition and removal of monomers from the end of a polymer, controlled by strand displacement logic. We capture the motivating feature of Bennett’s scheme — that physical reversibility corresponds to logically reversible computation, and arbitrarily little energy per computation step is required. Further, as a method of embedding logic control into chemical and biological systems, polymerbased chemical computation is significantly more efficient than geometryfree chemical reaction networks. 1
O.: Refining dynamics of gene regulatory networks in a stochastic πcalculus framework
 In: Transactions on Computational Systems Biology XIII
, 2011
"... Abstract. In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas ’ discrete parameters derives from this logical formalism. We offer a compositiona ..."
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Cited by 12 (9 self)
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Abstract. In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas ’ discrete parameters derives from this logical formalism. We offer a compositional approach which comes with a natural translation to the Stochastic πCalculus. The method we propose consists in successive refinements of generalized dynamics of Gene Regulatory Networks. We apply this method to the control of the differentiation in a Gene Regulatory Network generalizing metazoan segmentation processes. 1