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MOSBIE: a tool for comparison and analysis of rule-based biochemical models

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posted on 12.04.2016, 00:00 by John E. Jr Wenskovitch, Leonard A. Harris, Jose-Juan Tapia, James R. Faeder, G. Elisabeta Marai
Background: Mechanistic models that describe the dynamical behaviors of biochemical systems are common in computational systems biology, especially in the realm of cellular signaling. The development of families of such models, either by a single research group or by different groups working within the same area, presents significant challenges that range from identifying structural similarities and differences between models to understanding how these differences affect system dynamics. Results: We present the development and features of an interactive model exploration system, MOSBIE, which provides utilities for identifying similarities and differences between models within a family. Models are clustered using a custom similarity metric, and a visual interface is provided that allows a researcher to interactively compare the structures of pairs of models as well as view simulation results. Conclusions: We illustrate the usefulness of MOSBIE via two case studies in the cell signaling domain. We also present feedback provided by domain experts and discuss the benefits, as well as the limitations, of the approach.


This work has been supported by grant NSF-IIS-0952720, the Pitt Clinical Translational Science Institute (Fellows Program) 5UL1RR024153-05, and NIH/NIGMS grant P41GM103712.


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© 2014 Wenskovitch et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.





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