Quantitative model refinement as a solution to the combinatorial size explosion of biomodels

Elena Czeizler, Eugen Czeizler, Bogdan Iancu*, Ion Petre

*Corresponding author for this work

Research output: Book/Journal/ReportCommissioned reportProfessional


Building a large system through a systematic, step-by-step refinement of an ini-
tial abstract specification is a well established technique in software engineering,
not yet much explored in systems biology. In the case of systems biology, one
starts from an abstract, high-level model of a biological system and aims to add
more and more details about its reactants and/or reactions, through a number of
consecutive refinement steps. The refinement should be done in a quantitatively
correct way, so that (some of) the numerical properties of the model (such as the
experimental fit and validation) are preserved. In this study, we focus on the data-
refinement mechanism where the aim is to increase the level of details of some
of the reactants of a given model. That is, we analyse the case when a model is
refined by substituting a given species by several types of subspecies. We show in
this paper how the refined model can be systematically obtained from the original
one. As a case study for this methodology we choose a recently introduced model
for the eukaryotic heat shock response, [19]. We refine this model by including
details about the acetylation of the heat shock factors and its influence on the heat
shock response. The refined model has a significantly higher number of kinetic
parameters and variables. However, we show that our methodology allows us to
preserve the experimental fit/validation of the model with minimal computational
Original languageEnglish
Number of pages19
ISBN (Electronic)ISBN 978-952-12-2622-9
Publication statusPublished - 2011
MoE publication typeD4 Published development or research report or study


  • Model refinement, quantitative analysis, heat shock response, acetylation.


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