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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
A semantics, energy-based approach to automate biomodel composition
Niloofar Shahidi1, Michael Pan2,3,4, Kenneth Tran1
1Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Abstract:
Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.
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