If we consider the contact process with infection rate λ on a random graph on n vertices with
power law degree distributions, mean field calculations suggest that the critical value λ c of …

Graph embedding techniques are pivotal in real-world machine learning tasks that operate
on graph-structured data, such as social recommendation and protein structure modeling …

Belief propagation is a widely used message passing method for the solution of probabilistic
models on networks such as epidemic models, spin models, and Bayesian graphical …

Disclosing the main features of the structure of a network is crucial to understand a number
of static and dynamic properties, such as robustness to failures, spreading dynamics, or …

Recent observations of power‐law distributions in the connectivity of complex networks
came as a big surprise to researchers steeped in the tradition of random networks. Even …

Random (pseudo) graphs GN with the following structure are studied: first, independent and
identically distributed capacities Λi are drawn for vertices i= 1,…, N; then, each pair of …

A First Course in Systems Biology is an introduction for advanced undergraduate and
graduate students to the growing field of systems biology. Its main focus is the development …

We use real-world contact sequences, time-ordered lists of contacts from one person to
another, to study how fast information or disease can spread across network of contacts …

The analysis of protein-protein interactions is fundamental to the understanding of cellular
organization, processes, and functions. Recent large-scale investigations of protein-protein …

Online social networks have become ubiquitous to today's society and the study of data from
these networks has improved our understanding of the processes by which relationships …