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Although all biological research requires the use of abstract models, currently no standard method exists for describing the biological content of microscope images of tissues, in vitro experiments or in silico simulations of the tissue dynamics of multicellular systems.
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Firstly, due to the growing use of abstract modeling software, the reactions and the underlying reaction equations are usually available to us as abstract models, such as smbl[ 15], which we can analyze and manipulate analytically.
Here we consider the role of abstract models in advancing our understanding of movement pathology.
Semantic annotation of abstract models of actor ecosystem [45] could be used to derive executable process models that realise those systems.
Model-driven software engineering requires the refinement of abstract models into more concrete, platform-specific ones.
This group regards science as developing in an idealizational and dialectical manner, ideas that they trace back to Karl Marx's analysis of economics, inspired by his own study of Galileo's fruitful use of abstract, idealized models against the Aristotelians.
While partly answered using simple and abstract models, the question of the role of different aspects of model detail for controlling model outcomes still has not been explored with empirical ABMs.
In this work, we refer to precision measured w.r.t. the choice of abstract states, independently of the formalism used to describe abstract models.
The use of abstract concepts allows us to define the system behavior on higher levels.
In this paper, we explore and develop these concepts using a simple abstract model of symbiotic composition to examine its impact on evolvability.
Limitations of the abstract models will be discussed as well.
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