Title |
Challenges in horizontal model integration
|
---|---|
Published in |
BMC Systems Biology, March 2016
|
DOI | 10.1186/s12918-016-0266-3 |
Pubmed ID | |
Authors |
Katrin Kolczyk, Carsten Conradi |
Abstract |
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, 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. Obtaining 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. The 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. |
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Geographical breakdown
Country | Count | As % |
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Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 5 | 31% |
Student > Bachelor | 3 | 19% |
Student > Master | 3 | 19% |
Student > Ph. D. Student | 2 | 13% |
Professor > Associate Professor | 1 | 6% |
Other | 0 | 0% |
Unknown | 2 | 13% |
Readers by discipline | Count | As % |
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Computer Science | 4 | 25% |
Biochemistry, Genetics and Molecular Biology | 3 | 19% |
Engineering | 3 | 19% |
Mathematics | 1 | 6% |
Chemical Engineering | 1 | 6% |
Other | 2 | 13% |
Unknown | 2 | 13% |