Model integration - the process by which different modelling
efforts can be brought together to simulate the target system - is
a core technology in the field of Systems Biology. In the work
presented here model integration was addressed directly taking
cancer systems as an example. An in-depth literature review was
carried out to survey the model forms and types currently being
utilised. This was used to formalise the main challenges that model
integration poses, namely that of paradigm (the formalism on which
a model is based), focus (the real-world system the model
represents) and scale.
A two-tier model integration strategy, including a
knowledge-driven approach to address model semantics, was developed
to tackle these challenges. In the first step a novel description
of models at the level of behaviour, rather than the precise
mathematical or computational basis of the model, is developed by
distilling a set of abstract classes and properties. These can
accurately describe model behaviour and hence describe focus in a
way that can be integrated with behavioural descriptions of other
models. In the second step this behaviour is decomposed into an
agent-based system by translating the models into local interaction
rules.
The book provides a detailed and highly integrated presentation
of the method, encompassing both its novel theoretical and
practical aspects, which will enable the reader to practically
apply it to their model integration needs in academic research and
professional settings. The text is self-supporting. It also
includes an in-depth current bibliography to relevant research
papers and literature. The review of the current state of the art
in tumour modelling provides added value.
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