Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

The combination of the compactness of networks, featuring small diameters, and their
complex architectures results in a variety of critical effects dramatically different from those in …

The ultimate proof of our understanding of natural or technological systems is reflected in
our ability to control them. Although control theory offers mathematical tools for steering …

Background Elucidating gene regulatory networks is crucial for understanding normal cell
physiology and complex pathologic phenotypes. Existing computational methods for the …

This book presents a unified approach to a rich and rapidly evolving research domain at the
interface between statistical physics, theoretical computer science/discrete mathematics …

This is an extended version of my Nobel Lecture, delivered on December 8, 2021. I will
recall the genesis of the concept of multiple equilibria in natural sciences. I will then describe …

A reflection of our ultimate understanding of a complex system is our ability to control its
behavior. Typically, control has multiple prerequisites: it requires an accurate map of the …

Many questions of fundamental interest in today's science can be formulated as inference
problems: some partial, or noisy, observations are performed over a set of variables and the …

In this paper we extend our previous work on the stochastic block model, a commonly used
generative model for social and biological networks, and the problem of inferring functional …

We study the satisfiability of random Boolean expressions built from many clauses with K
variables per clause (K-satisfiability). Expressions with a ratio α of clauses to variables less …