Large scale models of physical phenomena demand the development of new statistical and
computational tools in order to be effective. Many such models are “sloppy,” ie, exhibit …

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 …

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

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 …

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 …

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 …

We present a novel and simple method to numerically calculate Fisher information matrices
for stochastic chemical kinetics models. The linear noise approximation is used to derive …

Dynamical systems modeling, particularly via systems of ordinary differential equations, has
been used to effectively capture the temporal behavior of different biochemical components …

Extensive and multi-dimensional data sets generated from recent cancer omics profiling
projects have presented new challenges and opportunities for unraveling the complexity of …

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 …