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

Sigmoid growth models, such as the logistic, Gompertz and Richards’ models, are widely
used to study population dynamics ranging from microscopic populations of cancer cells, to …

Tumour spheroid experiments are routinely used to study cancer progression and treatment.
Various and inconsistent experimental designs are used, leading to challenges in …

In vitro tumour spheroids have been used to study avascular tumour growth and drug design
for over 50 years. Tumour spheroids exhibit heterogeneity within the growing population …

Tumour spheroids are common in vitro experimental models of avascular tumour growth.
Compared with traditional two-dimensional culture, tumour spheroids more closely mimic the …

Tissue growth in three-dimensional (3D) printed scaffolds enables exploration and control
of cell behaviour in more biologically realistic geometries than that allowed by traditional 2D …

An enduring challenge in computational biology is to balance data quality and quantity with
model complexity. Tools such as identifiability analysis and information criterion have been …

Collective cell spreading takes place in spatially continuous environments, yet it is often
modelled using discrete lattice-based approaches. Here, we use data from a series of cell …

We present a novel framework to parameterise a mathematical model of cell invasion that
describes how a population of melanoma cells invades into human skin tissue. Using simple …

Acute myeloid leukaemia (AML) is a blood cancer affecting haematopoietic stem cells. AML
is routinely treated with chemotherapy, and so it is of great interest to develop optimal …