The advent of high-throughput genomics techniques, along with the completion of genome
sequencing projects, identification of protein–protein interactions and reconstruction of …

As malignant transformation requires synchronization of growth-driving signaling (S) and
metabolic (M) pathways, defining cancer-specific SM interconnected networks (SMINs) …

Motivation The elucidation of dysfunctional cellular processes that can induce the onset of a
disease is a challenging issue from both the experimental and computational perspectives …

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell
signaling has been summarized in signaling pathway databases, which, while useful, are …

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can
provide valuable insight. We propose a general method that can find the attractors of …

Although there is still some skepticism in the biological community regarding the value and
significance of quantitative computational modeling, important steps are continually being …

To simplify the analysis of Boolean networks, a reduction in the number of components is
often considered. A popular reduction method consists in eliminating components that are …

Motivation: Systems biology models can be used to test new hypotheses formulated on the
basis of previous knowledge or new experimental data, contradictory with a previously …

Highlights•Model calibration for mechanistic signaling models is well established.•An
appropriate objective function is pivotal for meaningful model calibration.•Robust …

Background A rapidly growing amount of knowledge about signaling and gene regulatory
networks is available in databases such as KEGG, Reactome, or RegulonDB. There is an …