Simple Summary The proposed research aims to provide a deep insight into the deep
learning and machine learning techniques used for diagnosing skin cancer. While …

Stochasticity is a key characteristic of intracellular processes such as gene regulation and
chemical signalling. Therefore, characterizing stochastic effects in biochemical systems is …

We examine the practical identifiability of parameters in a spatio-temporal reaction–diffusion
model of a scratch assay. Experimental data involve fluorescent cell cycle labels, providing …

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

The Fisher–Kolmogorov–Petrovsky–Piskunov model, also known as the Fisher–KPP model,
supports travelling wave solutions that are successfully used to model numerous invasive …

Reaction–diffusion models describing the movement, reproduction and death of individuals
within a population are key mathematical modelling tools with widespread applications in …

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

Highlights•Cancer is a heterogeneous and evolving disease, yet most drugs are
administered to simply give the maximum dose.•Treatment scheduling currently ignores the …

The extracellular matrix (ECM) is a highly complex structure through which biochemical and
mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a …

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 …