With the rising application of systems biology, sensitivity analysis methods have been widely
applied to study the biological systems, including metabolic networks, signalling pathways …

An increasing number of industrial bioprocesses capitalize on living cells by using them as
cell factories that convert sugars into chemicals. These processes range from the production …

This paper devotes to establishing a bridge between asymptotical stability of a probabilistic
Boolean network (PBN) and a solution to its induced equations, which are induced from the …

Whole-brain modeling of epilepsy combines personalized anatomical data with dynamical
models of abnormal activities to generate spatio-temporal seizure patterns as observed in …

Mathematical modeling is a key process to describe the behavior of biological networks.
One of the most difficult challenges is to build models that allow quantitative predictions of …

Data-driven models based on thermal resistor-capacitor networks (RC models) are useful in
enhancing the energy performance of buildings. This paper presents a simple yet effective …

Increasingly complex applications involve large datasets in combination with nonlinear and
high-dimensional mathematical models. In this context, statistical inference is a challenging …

Even though proteins are produced from mRNA, the correlation between mRNA levels and
protein abundances is moderate in most studies, occasionally attributed to complex post …

Dynamical systems describing whole cells are on the verge of becoming a reality. But as
models of reality, they are only useful if we have realistic parameters for the molecular …

The adaptive immune system is a dynamical, self-organized multiscale system that protects
vertebrates from both pathogens and internal irregularities, such as tumors. For these …