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

Mathematical models are routinely calibrated to experimental data, with goals ranging from
building predictive models to quantifying parameters that cannot be measured. Whether or …

Intracellular processes rarely work in isolation but continually interact with the rest of the cell.
In microbes, for example, we now know that gene expression across the whole genome …

As modeling becomes a more widespread practice in the life sciences and biomedical
sciences, researchers need reliable tools to calibrate models against ever more complex …

Cell size varies during the cell cycle and in response to external stimuli. This requires the
tight coordination, or" scaling," of mRNA and protein quantities with the cell volume in order …

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 …

Approximate Bayesian computation (ABC) has gained popularity over the past few years for
the analysis of complex models arising in population genetics, epidemiology and system …

Predictive mathematical models are a cornerstone of science and engineering. Yet
selecting, calibrating, and validating said science‐based models often remains an art in …

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 …

Complex networks, comprised of individual elements that interact with each other through
reaction channels, are ubiquitous across many scientific and engineering disciplines …