The success of new scientific areas can be assessed by their potential in contributing to new
theoretical approaches and in applications to real-world problems. Complex networks have …

In this paper we extract the topology of the semantic space in its encyclopedic acception,
measuring the semantic flow between the different entries of the largest modern …

Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges
interconnecting thousands of genes. We constructed a general human GRN from extensive …

Robustness to mutations and noise has been shown to evolve through stabilizing selection
for optimal phenotypes in model gene regulatory networks. The ability to evolve robust …

In this paper, we generalize a recently introduced expectation maximization (EM) method for
graphs and apply it to content-based networks. The EM method provides a classification of …

Both community detection and influence maximization are well-researched fields of network
science. Here, we investigate how several popular community detection algorithms can be …

Background A gene network's capacity to process information, so as to bind past events to
future actions, depends on its structure and logic. From previous and new microarray …

The dynamic stability of the Boolean networks representing a model for the gene
transcriptional regulation (Kauffman model) is studied by calculating analytically and …

A recent observation on an extensive collection of biological gene regulatory networks
suggests that the regulatory dynamics is tuned to remain close to the order-chaos boundary …

Emergence of properties at the system level, where these properties are not observed at the
individual entity level, is an important feature of complex systems. Biological system …