MOSBIE: A Tool for Comparison and Analysis of Rule-Based Biochemical Models
Researchers: G. Elisabeta Marai, John R. Wenskovitch, Leonard A. Harris, Jose-Juan Tapia, James R. Faeder
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 network models, either by a single research group or from multiple sources, presents signiﬁcant challenges that range from identifying functional structural diﬀerences to keeping track of the model history. We present the development and features of an interactive model exploration system, MOSBIE, which tracks the features and development history of a family of models and provides utilities for identifying similarities and diﬀerences between models. Models within a collection can be clustered using a custom similarity metric. We also provide a visual interface for exploring collections of models, allowing a researcher to interactively compare the similarities and diﬀerences between pairs of models, search for models which contain a given structural motif, and explore the parameters and simulations of models. We evaluate the usefulness of this system with a case study in the cell signaling domain. We present the feedback provided by domain experts, and discuss the beneﬁts of this approach.
Date: Unknown - Ongoing