Results 1  10
of
20
Stochastic Bigraphs
 MFPS 2008
, 2008
"... In this paper we present a stochastic semantics for Bigraphical Reactive Systems. A reduction and a labelled stochastic semantics for bigraphs are defined. As a sanity check, we prove that the two semantics are consistent with each other. We illustrate the expressiveness of the framework with an exa ..."
Abstract

Cited by 44 (13 self)
 Add to MetaCart
In this paper we present a stochastic semantics for Bigraphical Reactive Systems. A reduction and a labelled stochastic semantics for bigraphs are defined. As a sanity check, we prove that the two semantics are consistent with each other. We illustrate the expressiveness of the framework with an example of membrane budding in a biological system.
Lumpability Abstractions of Rulebased Systems
, 2010
"... The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial process in a mathematical model is an important challenge in systems biology. Exploiting the limited context on which m ..."
Abstract

Cited by 10 (4 self)
 Add to MetaCart
The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial process in a mathematical model is an important challenge in systems biology. Exploiting the limited context on which most binding and modification events are conditioned, attempts have been made to reduce the combinatorial complexity by quotienting the reachable set of molecular species, into species aggregates while preserving the deterministic semantics of the thermodynamic limit. Recently we proposed a quotienting that also preserves the stochastic semantics and that is complete in the sense that the semantics of individual species can be recovered from the aggregate semantics. In this paper we prove that this quotienting yields a sufficient condition for weak lumpability and that it gives rise to a backward Markov bisimulation between the original and aggregated transition system. We illustrate the framework on a case study of the EGF/insulin receptor crosstalk.
The graph grammar library  a generic framework for chemical graph rewrite systems
 THEORY AND PRACTICE OF MODEL TRANSFORMATIONS, PROC. OF ICMT 2013, VOLUME 7909 OF LNCS
, 2013
"... Graph rewrite systems are powerful tools to model and study complex problems in various fields of research. Their successful application to chemical reaction modelling on a molecular level was shown but no appropriate and simple system is available at the moment. The presented Graph Grammar Library ..."
Abstract

Cited by 5 (2 self)
 Add to MetaCart
(Show Context)
Graph rewrite systems are powerful tools to model and study complex problems in various fields of research. Their successful application to chemical reaction modelling on a molecular level was shown but no appropriate and simple system is available at the moment. The presented Graph Grammar Library (GGL) implements a generic Double Push Out approach for general graph rewrite systems. The framework focuses on a high level of modularity as well as high performance, using stateoftheart algorithms and data structures, and comes with extensive documentation. The large GGL chemistry module enables extensive and detailed studies of chemical systems. It well meets the requirements and abilities envisioned by Yadav et al. (2004) for such chemical rewrite systems. Here, molecules are represented as undirected labeled graphs while chemical reactions are described by according graph grammar rules. Beside the graph transformation, the GGL offers advanced cheminformatics algorithms for instance to estimate energies ofmolecules or aromaticity perception. These features are illustrated using a set of reactions from polyketide chemistry a huge class of natural compounds of medical relevance. The graph grammar based simulation of chemical reactions offered by the GGL is a powerful tool for extensive cheminformatics studies on a molecular level. The GGL already provides rewrite rules for all enzymes listed in the KEGG LIGAND database is freely available at
A model of sequential branching in hierarchical cell fate determination
 IEEE Transactions on Automatic Control, Special Issue on Systems Biology
, 2008
"... ..."
An Intuitive Automated Modelling Interface for Systems Biology
"... Modelling of biological systems by mathematical and computational techniques is becoming increasingly widespread in research on biological systems. However, expressing biological knowledge in specialised modelling languages often requires a simultaneous understanding of the considered biological sys ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
Modelling of biological systems by mathematical and computational techniques is becoming increasingly widespread in research on biological systems. However, expressing biological knowledge in specialised modelling languages often requires a simultaneous understanding of the considered biological system and expert knowledge of the modelling language. Isolating and communicating the biological knowledge to build models for simulation and analysis is a challenging task both for wetlab biologists and modellers. Writing programs in simulation languages requires specialised training, and it is difficult even for the experts when complex interactions between biochemical species in biological systems are considered: the representation of different states of a biochemical species with respect to all its interaction capabilities results in an exponential blow up in the number of states. For example, when a protein with n different interaction sites is being modelled, this results in 2 n states, which needs to be represented in the model. Enumerating all these states by hand, also without inserting typos is a difficult task. Process algebras are languages that have originally been designed to formally describe complex reactive computer systems. Due to the resemblance between these computer systems and biological systems, process algebra have been recently used to model biological systems. An important feature of the process algebra languages is the possibility to describe the components of a system separately and observe the emergent behaviour from the interactions of the components. To this end, we introduce an intuitive frontend interface language to biological models and a tool for automated translation
How liquid is biological signalling?
, 2008
"... This paper proposes an investigation of the global statistics of synthetic protein networksa step towards a systemic understanding of their design space. We derive a liquidity index which describes the onset of the phase transition where an ensemble of agents aggregates into a giant cluster. This i ..."
Abstract

Cited by 2 (2 self)
 Add to MetaCart
This paper proposes an investigation of the global statistics of synthetic protein networksa step towards a systemic understanding of their design space. We derive a liquidity index which describes the onset of the phase transition where an ensemble of agents aggregates into a giant cluster. This index captures the influence of both the domain distribution of agents and the binding strengths of their various domains in the limit of infinite populations. In simple cases it is possible to derive an explicit analytical expression of this index, which allows to compare with simulations, and get a sense of how it transfers to the concrete finite case.
Complex Functional Rates in Rulebased Languages for Biochemistry
 Transactions on Computational Systems Biology
"... Rulebased languages (like, for example, Kappa, BioNetGen, and BioCham) have emerged as successful models for the representation, analysis, and simulation of biochemical systems. In particular Kappa, although based on reactions, differs from traditional chemistry as it allows for a graphlike repre ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
Rulebased languages (like, for example, Kappa, BioNetGen, and BioCham) have emerged as successful models for the representation, analysis, and simulation of biochemical systems. In particular Kappa, although based on reactions, differs from traditional chemistry as it allows for a graphlike representation of complexes. It follows the “don’t care, don’t write ” approach: a rule contains the description of only those parts of the complexes that are actually involved in a reaction. Hence, given any possible combination of complexes that contain the reactants, such complexes can give rise to the reaction. In this paper we address the problem of extending the “don’t care, don’t write ” approach to cases in which the actual structure of the complexes involved in the reaction could affect it (for instance, the mass of the complexes could influence the rate). The solutions that we propose is κF, an extension of the Kappacalculus in which rates are defined as functions of the actually involved complexes.
Rulebased modelling and tunable resolution
 Electron. Proc. Theor. Comput. Sci
, 2009
"... ..."
(Show Context)
An Intuitive Modelling Interface for Systems Biology
, 2009
"... We introduce a natural language interface for building stochastic π calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochem ..."
Abstract
 Add to MetaCart
We introduce a natural language interface for building stochastic π calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochemical systems modularly by describing their dynamics in a narrativestyle language, while making amendments, refinements and extensions on the models easy. We give a formal semantics for this language and a translation algorithm into stochastic π calculus that delivers this semantics. We demonstrate the language on a model of Fcγ receptor phosphorylation during phagocytosis. We provide a tool implementation of the translation into a stochastic π calculus language, Microsoft Research’s SPiM, which can be used for simulation and analysis.