Estimating parameters of a stochastic cell invasion model with fluorescent cell cycle labelling using approximate Bayesian computation
MJ Carr, MJ Simpson… - Journal of the Royal …, 2021 - royalsocietypublishing.org
We develop a parameter estimation method based on approximate Bayesian computation
(ABC) for a stochastic cell invasion model using fluorescent cell cycle labelling with …
(ABC) for a stochastic cell invasion model using fluorescent cell cycle labelling with …
Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation
Wound healing and tumour growth involve collective cell spreading, which is driven by
individual motility and proliferation events within a population of cells. Mathematical models …
individual motility and proliferation events within a population of cells. Mathematical models …
Stochastic models of cell invasion with fluorescent cell cycle indicators
Fluorescent cell cycle labelling in cell biology experiments provides real time information
about the location of individual cells, as well as the phase of the cell cycle of individual cells …
about the location of individual cells, as well as the phase of the cell cycle of individual cells …
Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth
Hybrid multiscale agent-based models (ABMs) are unique in their ability to simulate
individual cell interactions and microenvironmental dynamics. Unfortunately, the high …
individual cell interactions and microenvironmental dynamics. Unfortunately, the high …
Practical parameter identifiability for spatio-temporal models of cell invasion
MJ Simpson, RE Baker… - Journal of the …, 2020 - royalsocietypublishing.org
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 …
model of a scratch assay. Experimental data involve fluorescent cell cycle labels, providing …
Melanoma cell colony expansion parameters revealed by approximate Bayesian computation
In vitro studies and mathematical models are now being widely used to study the underlying
mechanisms driving the expansion of cell colonies. This can improve our understanding of …
mechanisms driving the expansion of cell colonies. This can improve our understanding of …
Calibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation
Agent-based models (ABMs) are readily used to capture the stochasticity in tumour
evolution; however, these models are often challenging to validate with experimental …
evolution; however, these models are often challenging to validate with experimental …
A Bayesian computational approach to explore the optimal duration of a cell proliferation assay
Cell proliferation assays are routinely used to explore how a low-density monolayer of cells
grows with time. For a typical cell line with a doubling time of 12 h (or longer), a standard cell …
grows with time. For a typical cell line with a doubling time of 12 h (or longer), a standard cell …
Approximate Bayesian computation reveals the importance of repeated measurements for parameterising cell-based models of growing tissues
The growth and dynamics of epithelial tissues govern many morphogenetic processes in
embryonic development. A recent quantitative transition in data acquisition, facilitated by …
embryonic development. A recent quantitative transition in data acquisition, facilitated by …
Using approximate bayesian computation to quantify cell–cell adhesion parameters in a cell migratory process
In this work, we implement approximate Bayesian computational methods to improve the
design of a wound-healing assay used to quantify cell–cell interactions. This is important as …
design of a wound-healing assay used to quantify cell–cell interactions. This is important as …