Quantitative model refinement in four different frameworks, with applications to the heat shock response

A3 Bokavsnitt, kapitel i forskningsböcker


Interna författare/redaktörer


Publikationens författare: Diana-Elena Gratie, Bogdan Iancu, Sepinoud Azimi, Ion Petre
Redaktörer: Luigia Petre, Emil Sekerinski
Publiceringsår: 2016
Förläggare: CRC Press
Moderpublikationens namn: From Action Systems to Distributed Systems
Artikelns första sida, sidnummer: 201
Artikelns sista sida, sidnummer: 214
ISBN: 978-1-4987-0158-7
eISBN: 978-1-4987-0159-4


Abstrakt

Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural
aspect of the refinement defines an increase in the resolution of its representation, while the
quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the
specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.
Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.

Senast uppdaterad 2019-21-11 vid 03:55