Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …

Resilience, a system's ability to adjust its activity to retain its basic functionality when errors,
failures and environmental changes occur, is a defining property of many complex systems …

High-throughput technologies, offering an unprecedented wealth of quantitative data
underlying the makeup of living systems, are changing biology. Notably, the systematic …

Many systems on our planet shift abruptly and irreversibly from the desired state to an
undesired state when forced across a “tip** point”. Some examples are mass extinctions …

The problem of reconstructing nonlinear and complex dynamical systems from measured
data or time series is central to many scientific disciplines including physical, biological …

A major achievement in the study of complex networks is the realization that diverse
systems, from sub-cellular biology to social networks, exhibit universal topological …

The availability of empirical data that capture the structure and behaviour of complex
networked systems has been greatly increased in recent years; however, a versatile …

Graph theory is now becoming a standard tool in system-level neuroscience. However,
endowing observed brain anatomy and dynamics with a complex network structure does not …

Although networks are extensively used to visualize information flow in biological, social and
technological systems, translating topology into dynamic flow continues to challenge us, as …