Multifacetted modelling and discrete event simulation
Multifacetted modelling and discrete event simulation
Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Implementation of logic functions and computations by chemical kinetics
Physica D - Special issue originating from the international workshop on dynamism and regulation in nonlinear chemical systems
Communicating and mobile systems: the &pgr;-calculus
Communicating and mobile systems: the &pgr;-calculus
Modeling and simulation of mobile agents
Future Generation Computer Systems
Dynamic structures in modeling and simulation: a reflective approach
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Continuous System Modeling
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Computational Challenges in Cell Simulation: A Software Engineering Approach
IEEE Intelligent Systems
A component-based approach to modeling and simulating mixed-signal and hybrid systems
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Modelling Blood Vessels of the Eye with Parametric L-Systems Using Evolutionary Algorithms
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Social Science Microsimulation [Dagstuhl Seminar, May, 1995]
CMSB '03 Proceedings of the First International Workshop on Computational Methods in Systems Biology
Formal Modeling of C. elegans Development: A Scenario-Based Approach
CMSB '03 Proceedings of the First International Workshop on Computational Methods in Systems Biology
Visual Programming for Modeling and Simulation of Biomolecular Regulatory Networks
HiPC '02 Proceedings of the 9th International Conference on High Performance Computing
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Applied system simulation
BioAmbients: an abstraction for biological compartments
Theoretical Computer Science - Special issue: Computational systems biology
Towards biopathway modeling and simulation
ICATPN'03 Proceedings of the 24th international conference on Applications and theory of Petri nets
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
The biochemical abstract machine BIOCHAM
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
General stochastic hybrid method for the simulation of chemical reaction processes in cells
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
Challenges for modeling and simulation methods in systems biology
Proceedings of the 38th conference on Winter simulation
Modelling, property verification and behavioural equivalence of lactose operon regulation
Computers in Biology and Medicine
Electronic Notes in Theoretical Computer Science (ENTCS)
A computational framework for modelling multicellular biochemistry
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An extendable system for conceptual modeling and simulation of signal transduction pathways
ER'07 Proceedings of the 2007 conference on Advances in conceptual modeling: foundations and applications
A Framework for Modelling and Simulating Networks of Cells
Electronic Notes in Theoretical Computer Science (ENTCS)
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Diverse modeling and simulation methods are being applied in the area of Systems Biology. Most models in Systems Biology can easily be located within the space that is spanned by three dimensions of modeling: continuous and discrete; quantitative and qualitative; stochastic and deterministic. These dimensions are not entirely independent nor are they exclusive. Many modeling approaches are hybrid as they combine continuous and discrete, quantitative and qualitative, stochastic and deterministic aspects. Another important aspect for the distinction of modeling approaches is at which level a model describes a system: is it at the “macro” level, at the “micro” level, or at multiple levels of organization. Although multi-level models can be located anywhere in the space spanned by the three dimensions of modeling and simulation, clustering tendencies can be observed whose implications are discussed and illustrated by moving from a continuous, deterministic quantitative macro model to a stochastic discrete-event semi-quantitative multi-level model.