Modeling of Molecular Networks

Abstract

In biomolecular systems, various non-identical molecules interact in diverse ways. The field of systems biology aims to understand how the components and interactions of biological systems give rise to the system’s behavior and phenotypes. Researchers have used molecular networks and dynamic models to represent and understand biological systems. In this chapter, we introduce the network representation and the graph measures that quantify its topological properties. We describe how to build a discrete dynamic (Boolean) model of a biological system from experimental data, and how to use the model to provide insights into emergent phenomena and make useful predictions. We also introduce methods to bridge the network’s topological and dynamical properties. We use real biological system involved in complex disease to demonstrate the theoretical framework. Discrete dynamical models, especially Boolean networks, benefit from the current high-throughput technologies and large amounts of qualitative data and provide insight to large-scale systems, where continuous modeling is not possible yet.