A group theoretic approach to model comparison with simplicial representations
Sean T. Vittadello, Michael P.H. Stumpf

TL;DR
This paper develops a group-theoretic framework for comparing biological models represented as simplicial complexes, enabling automated and rigorous identification of equivalent model components to unify diverse biological system models.
Contribution
It introduces a novel, automatable method for model comparison using vertex symmetry and group actions on simplicial complexes, and offers an alternative group-based representation for models.
Findings
Automated identification of conceptually related model components.
Simplification of model equivalence determination.
Framework for applying group-theoretic techniques to model comparison.
Abstract
The complexity of biological systems, and the increasingly large amount of associated experimental data, necessitates that we develop mathematical models to further our understanding of these systems. As biological systems are generally not well understood, most mathematical models of these systems are based on experimental data, resulting in a seemingly heterogeneous collection of models that ostensibly represent the same system. To understand the system we therefore need to know how the different models are related, with a view to obtaining a unified mathematical description. This goal is complicated by the fact that distinct mathematical formalisms may be used to represent the same system, making direct comparison of the models very difficult. In previous work we developed an appropriate framework for model comparison where we represent models as labelled simplicial complexes and…
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Taxonomy
TopicsGene Regulatory Network Analysis · Bioinformatics and Genomic Networks · Microbial Metabolic Engineering and Bioproduction
