Multilayer modeling and analysis of complex biological systems

Abstract

Complex systems are characterized by constituents -- from neurons in the brain to individuals in a social network -- which exhibit special structural organization and nonlinear dynamics. As a consequence, a complex system can not be understood by studying its units separately because their interactions lead to unexpected emerging phenomena, from collective behavior to phase transitions. In the last decade, we have discovered that a new level of complexity characterizes a variety of natural and artificial systems, either where homogeneous units simultaneously interact in distinct ways or where interdependency between heterogeneous units or sub-systems emerge. The unprecedented newfound wealth of data allows to characterize such systems by defining distinct "layers", each one encoding a different network representation of the system. The result is a multilayer network model. In this talk we will introduce the most salient features of multilayer systems in terms of their structural representation and dynamical processes, and discuss some practical applications to biological networks of interest for systems biology and systems medicine, while discussing opportunities and limitations affecting network reconstruction and analysis in general.