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Selforganized patterning by diffusible factors: roles of a community effect
 Fundamenta Informaticae
, 2012
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Bigraphical Languages and their Simulation
"... We study bigraphs as a foundation for practical formal languages and the problem of simulating such bigraphical languages. The theory of bigraphs is a foundational, graphical model of concurrent systems focusing on mobility and connectivity. It is a metamodel in the sense that it is parametrized ov ..."
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We study bigraphs as a foundation for practical formal languages and the problem of simulating such bigraphical languages. The theory of bigraphs is a foundational, graphical model of concurrent systems focusing on mobility and connectivity. It is a metamodel in the sense that it is parametrized over a signature and a set of reaction rules which determine the syntax and dynamic semantics, respectively. This allows for rather direct models and, together with a natural yet formal graphical notation and an elegant theory of behavioral equivalence, this makes bigraphs an enticing foundation for practical formal languages. However, the theory of bigraphs is still young. While direct models of many process calculi have been constructed, it is unclear how suitable bigraphs are for more practical formal languages. Also, the generality of bigraphs comes at a price of complexity in the theory and simulation of bigraphical models is nontrivial. A key problem is that of matching: deciding if and how a reaction rule applies to a bigraph. In this dissertation, we study bigraphs and their simulation for two types of practical formal languages: programming languages and languages for cell biology. First, we study programming languages and binding bigraphs, a variant of bigraphs with a facility for modeling the binders found in most programming languages. Building on an existing
Constructing and Visualizing Chemical Reaction Networks from PiCalculus Models
, 2012
"... Abstract. The πcalculus, in particular its stochastic version the stochastic πcalculus, is a common modeling formalism to concisely describe the chemical reactions occurring in biochemical systems. However, it remains largely unexplored how to transform a biochemical model expressed in the stochas ..."
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Abstract. The πcalculus, in particular its stochastic version the stochastic πcalculus, is a common modeling formalism to concisely describe the chemical reactions occurring in biochemical systems. However, it remains largely unexplored how to transform a biochemical model expressed in the stochastic πcalculus back into a set of meaningful reactions. To this end, we present a two step approach of first translating model states to reaction sets and then visualizing sequences of reaction sets, which are obtained from state trajectories, in terms of reaction networks. Our translation from model states to reaction sets is formally defined and shown to be correct, in the sense that it reflects the states and transitions as they are derived from the continuous time Markov chainsemantics of the stochastic πcalculus. Our visualization concept combines high level measures of network complexity with interactive, tablebased network visualizations. It directly reflects the structures introduced in the first step and allows modelers to explore the resulting simulation traces by providing both: an overview of a network’s evolution and a detail inspection on demand.
Computational Modeling, Formal Analysis, and Tools for Systems Biology
, 2016
"... As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biolo ..."
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As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.
METHODOLOGY ARTICLE Open Access
"... Rulebased multilevel modeling of cell biological systems ..."
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Complex Functional Rates in the Modeling of Nano Devices (Extended abstract)
, 2013
"... We give an overview of recent work on the rulebased modeling of nano devices. In particular, our experience in the modeling of a nanoscale elevator suggested us to enhance rulebased modeling with complex functional rates that can be used to express rates that depend on the current state of the ent ..."
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We give an overview of recent work on the rulebased modeling of nano devices. In particular, our experience in the modeling of a nanoscale elevator suggested us to enhance rulebased modeling with complex functional rates that can be used to express rates that depend on the current state of the entire complexes in which the reacting molecules reside.
Structural simplification of chemical reaction networks
, 2015
"... preserving deterministic semantics ..."
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