1471-2105-15-316.pdf (3.04 MB)
MOSBIE: a tool for comparison and analysis of rule-based biochemical models
journal contribution
posted on 2016-04-12, 00:00 authored by John E. Jr Wenskovitch, Leonard A. Harris, Jose-Juan Tapia, James R. Faeder, G. Elisabeta MaraiBackground: 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.
Funding
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.
History
Publisher Statement
© 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.Language
- en_US
issn
1471-2105Issue date
2014-01-01Usage metrics
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