MOSBIE: a tool for comparison and analysis of rule-based biochemical models |
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Authors: | John E Wenskovitch Jr Leonard A Harris Jose-Juan Tapia James R Faeder G Elisabeta Marai |
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Institution: | .Department of Computer Science, Allegheny College, 16335 Meadville, PA USA ;.Department of Cancer Biology, Vanderbilt University School of Medicine, 37232 Nashville, TN USA ;.Department of Computational and Systems Biology, University of Pittsburgh, 15260 Pittsburgh, USA ;.Electronic Visualization Lab, Department of Computer Science, University of Illinois at Chicago, 60607 Chicago, USA |
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Abstract: | BackgroundMechanistic 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.ResultsWe 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.ConclusionsWe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-316) contains supplementary material, which is available to authorized users. |
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Keywords: | Visualization Visual computing Rule-based modeling Cell signaling |
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