Abstract Systems biology has to increasingly cope with large-and multi-scale biological
systems. Many successful in silico representations and simulations of various cellular …

A complication is an unanticipated disease arisen following, induced by a disease, a
treatment or a procedure. We compile a human disease-complication network from the …

Background Computational models of cell signaling networks are extremely useful tools for
the exploration of underlying system behavior and prediction of response to various …

Over the past several decades, mathematical modeling has been applied to increasingly
wider scopes of questions in drug development. Accordingly, the range of modeling tools …

Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms
giving rise to highly complex and cell-context specific signaling networks. Dissecting the …

Boolean models have been instrumental in predicting general features of gene networks
and more recently also as explorative tools in specific biological applications. In this study …

Background Many structural centrality measures were proposed to predict putative disease
genes on biological networks. Closeness is one of the best-known structural centrality …

Engineered nanoparticles (NPs) have been widely demonstrated to induce toxic effects to
various cell types. In vitro cell exposure systems have high potential for reliable, high …

The metabolic modelling community has established the gold standard for bottom-up
systems biology with reconstruction, validation and simulation of mechanistic genome-scale …

Mathematical models of biochemical reaction networks are important tools in systems
biology and systems medicine to understand the reasons for diseases like cancer, and to …