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The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.
Motivation: Network modelling in systems biology has become an important tool to study molecular interactions in cancer research, because understanding the interplay of proteins is necessary for developing novel drugs and therapies.
Modelling in systems biology often builds on the study of time-dependent phenomena.
In fact, the meaning facets framework establishes a new methodology for computer-aided collaborative modelling in Systems Biology.
Computer-aided modelling in Systems Biology will be impossible until the meaning of the models is formally described.
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If modeled in Systems Biology Markup Language (SBML, Hucka et al., 2003), the velocity of a reaction depends on the concentration of its educts, products and modifiers.
Twenty-seven phones were modeled in this system.
Nowadays most models in systems engineering are created with the UML as standardized set of notations.
One area where combined explanations for developmental phenomena are being analyzed pertains to mechanism descriptions and mathematical modeling in systems biology (Brigandt 2013; Fagan 2013).
Many models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available.
Data and models in systems biology investigations are inherently interlinked.
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