Network science has evolved into an indispensable platform for studying complex systems.
But recent research has identified limits of classical networks, where links connect pairs of …

The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

Over the past decade, the use of networks has led to a new modelling paradigm combining
several branches of science, including physics, mathematics, biology and social sciences …

Networks allow us to describe a wide range of interaction phenomena that occur in complex
systems arising in such diverse fields of knowledge as neuroscience, engineering, ecology …

A network is a typical expressive form of representing complex systems in terms of vertices
and links, in which the pattern of interactions amongst components of the network is intricate …

Higher-order interactions have significant implications for the dynamics of competing
epidemic spreads. In this paper, a competing spread model for two simplicial irreversible …

New disease challenges, societal demands and better or novel types of data, drive
innovations in the structure, formulation and analysis of epidemic models. Innovations in …

Edges are the most basic structures in complex networks, representing relationships of node
pairs. However, many higher-order interactions in reality are beyond node-to-node …

Synaptic connectivity between neocortical neurons is highly structured. The network
structure of synaptic connectivity includes first-order properties that can be described by …

Designing algorithms that generate networks with a given degree sequence while varying
both subgraph composition and distribution of subgraphs around nodes is an important but …