Employing Power Graph Analysis to Facilitate Modeling Molecular Interaction Networks

Abstract

Mathematical modeling is used to explore and understand complex systems ranging from weather patterns to social networks to gene-expression regulatory mechanisms. There is an upper limit to the amount of details that can be reflected in a model imposed by finite computational resources. Thus, there are methods to reduce the complexity of the modeled system to its most significant parameters. We discuss the suitability of clustering techniques, in particular Power Graph Analysis as an intermediate step of modeling.

Keywords

• Power graph analysis
• Molecular interaction networks
• Dynamic system