Complex networks have become the main paradigm for modelling the dynamics of
interacting systems. However, networks are intrinsically limited to describing pairwise …

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 …

Protein interactions form a complex dynamic molecular system that shapes cell phenotype
and function; in this regard, network analysis is a powerful tool for studying the dynamics of …

Hypergraphs are used in machine learning to model higher-order relationships in data.
While spectral methods for graphs are well-established, spectral theory for hypergraphs …

Higher-order interactions are ubiquitous in the real world and play a critical role in
maintaining the overall function of complex systems. To investigate the effects of higher …

We investigate the dynamical evolution of Stuart-Landau oscillators globally coupled
through conjugate or dissimilar variables on simplicial complexes. We report a first-order …

Leveraging hypergraph structures to model advanced processes has gained much attention
over the last few years in many areas, ranging from protein-interaction in computational …

Timely identification of adverse drug reactions (ADRs) is highly important in the domains of
public health and pharmacology. Early discovery of potential ADRs can limit their effect on …

Network biology, an interdisciplinary field at the intersection of computational and biological
sciences, is critical for deepening understanding of cellular functioning and disease. While …

Analyses of ecological network structure have yielded important insights into the functioning
of complex ecological systems. However, such analyses almost universally omit non …