Molecular mechanisms of health and disease are often represented as systems biology
diagrams, and the coverage of such representation constantly increases. These static …

Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data
to control cell phenotypes and design interventions that reverse pathological states lags …

Motivation Mathematical models of biological processes altered in cancer are built using the
knowledge of complex networks of signaling pathways, detailing the molecular regulations …

Inference of gene regulatory networks has been an active area of research for around 20
years, leading to the development of sophisticated inference algorithms based on a variety …

In systems biology, mathematical models and simulations play a crucial role in
understanding complex biological systems. Different modelling frameworks are employed …

Boolean modelling of gene regulation but also of post-transcriptomic systems has proven
over the years that it can bring powerful analyses and corresponding insight to the many …

Genomics studies routinely confront researchers with long lists of tumor alterations detected
in patients. Such lists are difficult to interpret since only a minority of the alterations are …

We describe a strategy for the development of a rational approach of neoplastic disease
therapy based on the demonstration that scale-free networks are susceptible to specific …

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability
to mediate inflammatory responses of the immune system. Given the critical role of DCs in …

A Boolean network (BN) is a discrete dynamical system defined by a Boolean function that
maps to the domain itself. A trap space of a BN is a generalization of a fixed point, which is …