Methods for Structural Inference and Functional Module Identification in Intracellular Networks

TL;DR: This chapter provides an overview of the analytical approaches and computational tools that have been applied to biological systems in order to describe them at different levels of abstraction and reviews methods that model or infer a topological map of complex biological networks.

Abstract: The ways in which intracellular components interact in order to produce certain functions remains a mystery to the scientific community. Although parts of biological systems become more and more characterized, a more global understanding of the structure, dynamics and functionalities of complex intracellular networks is currently lacking. Systems Biology approaches aim at providing such a global picture by combining analytical and experimental techniques across several multi-disciplinary fields. In this chapter, we provide an overview of the analytical approaches and computational tools that have been applied to biological systems in order to describe them at different levels of abstraction. We start by reviewing methods that model or infer a topological map of complex biological networks (structural inference) and move on to discuss ways of discovering the functionalities of sub-network entities that comprise these networks (functional module inference). Although clearly not exclusive, this chapter aims at providing a representative overview of the currently available methods that have been successfully used to characterize complex biological networks and reveal their structure and function.