Multilayer Network Modeling of Integrated Biological Systems

TL;DR

This paper emphasizes the importance of multilayer network models for accurately representing the complex, multi-scale interactions in biological systems, moving beyond simple network aggregations to capture dynamic interdependencies.

Contribution

It introduces the concept of multilayer networks as a superior framework for modeling biological systems' intricate relationships across different scales and time.

Findings

Multilayer networks better capture biological complexity.

Simple networks overlook critical interdependencies.

Multilayer modeling enhances understanding of biological interactions.

Abstract

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks -- obtained by aggregating or neglecting temporal or categorical description of biological data -- are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.