The functioning of many biochemical networks is often robust—remarkably stable under
changes in external conditions and internal reaction parameters. Much recent work on …

The interdisciplinary field of systems biology has evolved rapidly over the last years.
Different disciplines have aided the development of both its experimental and theoretical …

Physicochemical models of signaling pathways are characterized by high levels of structural
and parametric uncertainty, reflecting both incomplete knowledge about signal transduction …

Like engineering systems, biological systems must also operate effectively in the presence
of internal and external uncertainty—such as genetic mutations or temperature changes, for …

The lack of standardization in the way that quantitative and systems pharmacology (QSP)
models are developed, tested, and documented hinders their reproducibility, reusability, and …

The engineering of transcriptional networks presents many challenges due to the inherent
uncertainty in the system structure, changing cellular context, and stochasticity in the …

Experimental design for cellular networks based on sensitivity analysis is studied in this
work. Both optimal and robust experimental design strategies are developed for the IκB‐NF …

Despite their complexity, biological systems are able to endure huge parameter fluctuations
and survive in the most diverse environmental conditions. Mathematical tools from graph …

Vital physiological behaviors exhibited daily by bacteria, plants, and animals are governed
by endogenous oscillators called circadian clocks. The most salient feature of the circadian …

Mathematical models of biochemical reaction networks are important tools in systems
biology and systems medicine, eg, to analyze disease causes or to make predictions for the …