Identifiability analysis for stochastic differential equation models in systems biology
Mathematical models are routinely calibrated to experimental data, with goals ranging from
building predictive models to quantifying parameters that cannot be measured. Whether or …
building predictive models to quantifying parameters that cannot be measured. Whether or …
Implementing measurement error models with mechanistic mathematical models in a likelihood-based framework for estimation, identifiability analysis and prediction …
RJ Murphy, OJ Maclaren… - Journal of the Royal …, 2024 - royalsocietypublishing.org
Throughout the life sciences, we routinely seek to interpret measurements and observations
using parametrized mechanistic mathematical models. A fundamental and often overlooked …
using parametrized mechanistic mathematical models. A fundamental and often overlooked …
Parameter identifiability and model selection for sigmoid population growth models
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 …
used to study population dynamics ranging from microscopic populations of cancer cells, to …
Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art
Stochasticity is a key characteristic of intracellular processes such as gene regulation and
chemical signalling. Therefore, characterizing stochastic effects in biochemical systems is …
chemical signalling. Therefore, characterizing stochastic effects in biochemical systems is …
Using experimental data and information criteria to guide model selection for reaction–diffusion problems in mathematical biology
Reaction–diffusion models describing the movement, reproduction and death of individuals
within a population are key mathematical modelling tools with widespread applications in …
within a population are key mathematical modelling tools with widespread applications in …
Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth
RJ Murphy, OJ Maclaren… - Journal of the …, 2022 - royalsocietypublishing.org
Throughout the life sciences, biological populations undergo multiple phases of growth,
often referred to as biphasic growth for the commonly encountered situation involving two …
often referred to as biphasic growth for the commonly encountered situation involving two …
Mathematical models for cell migration with real-time cell cycle dynamics
The fluorescent ubiquitination-based cell cycle indicator, also known as FUCCI, allows the
visualization of the G1 and S/G2/M cell cycle phases of individual cells. FUCCI consists of …
visualization of the G1 and S/G2/M cell cycle phases of individual cells. FUCCI consists of …
3D bioprinting of a trachea-mimetic cellular construct of a clinically relevant size
Despite notable advances in extrusion-based 3D bioprinting, it remains a challenge to
create a clinically-sized cellular construct using extrusion-based 3D printing due to long …
create a clinically-sized cellular construct using extrusion-based 3D printing due to long …
Autocrine signaling can explain the emergence of Allee effects in cancer cell populations
In many human cancers, the rate of cell growth depends crucially on the size of the tumor
cell population. Low, zero, or negative growth at low population densities is known as the …
cell population. Low, zero, or negative growth at low population densities is known as the …
Inferring parameters for a lattice-free model of cell migration and proliferation using experimental data
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 …
modelled using discrete lattice-based approaches. Here, we use data from a series of cell …