Abstract
BackgroundSystems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field.ResultsObtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model.ConclusionsThe reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0266-3) contains supplementary material, which is available to authorized users.
Highlights
Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control
Model integration may potentially speed up the systems biology cycle of modeling and experimentation by re-using the data that was explained by the individual models
To illustrate challenges and solutions arising in behavioral integration, two models describing epidermal growth factor (EGF) and nerve growth factor (NGF) signaling originally presented in [10] are integrated
Summary
Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Answering new and even more complex biomedical questions requires models of complete cells, organs or even organisms. An arguably very efficient approach to obtain such models is to combine or integrate existing models. Model integration may potentially speed up the systems biology cycle of modeling and experimentation by re-using the data that was explained by the individual models. By combining existing data and models one may obtain an integrated model of enhanced predictive power
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