The interplay of mathematical modelling with experiments is one of the central elements in
systems biology. The aim of reverse engineering is to infer, analyse and understand …

Reliably diagnosing faults and malfunctions has become increasingly challenging in
modern technical systems because of their growing complexity as well as increasingly …

Our understanding of most biological systems is in its infancy. Learning their structure and
intricacies is fraught with challenges, and often side-stepped in favour of studying the …

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 …

Various types of biological knowledge describe networks of interactions among elementary
entities. For example, transcriptional regulatory networks consist of interactions among …

Real-time diagnostics of cold atmospheric plasma (CAP) sources can be challenging due to
the requirement for expensive equipment and complicated analysis. Data analytics that rely …

The size and complexity of cellular systems make building predictive models an extremely
difficult task. In principle dynamical time-course data can be used to elucidate the structure …

Objective Breast cancer is a global health concern that demands attention. In our
contribution to addressing this disease, our study focuses on investigating a wireless micro …

Dynamic models formulated as a set of ordinary differential equations provide a detailed
description of the time-evolution of a system. Such models of (bio) chemical reaction …

Accurate measurements of metabolic fluxes in living cells are central to metabolism research
and metabolic engineering. The gold standard method is model-based metabolic flux …