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Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process

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Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process. / Ross, Robert; Baker, Ruth; Ford, Matthew et al.
In: Biorxiv, 24.08.2016.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Ross R, Baker R, Ford M, Mort R, Yates C. Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process. Biorxiv. 2016 Aug 24;068791. doi: 10.1101/068791

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Ross, Robert ; Baker, Ruth ; Ford, Matthew et al. / Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process. In: Biorxiv. 2016.

Bibtex

@article{4811c6371e7e4cab9da453ba0f8c2559,
title = "Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process",
abstract = "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 cell-cell interactions, such as adhesion and repulsion, have been shown to play an important role in cell migration. Initially, we demonstrate with a model of an ideal experiment that we are able to identify model parameters for agent motility and adhesion, given we choose appropriate summary statistics. Following this, we replace our model of an ideal experiment with a model representative of a practically realisable experiment. We demonstrate that, given the current (and commonly used) experimental set-up, model parameters cannot be accurately identified using approximate Bayesian computation methods. We compare new experimental designs through simulation, and show more accurate identification of model parameters is possible by expanding the size of the domain upon which the experiment is performed, as opposed to increasing the number of experimental repeats. The results presented in this work therefore describe time and cost-saving alterations for a commonly performed experiment for identifying cell motility parameters. Moreover, the results presented in this work will be of interest to those concerned with performing experiments that allow for the accurate identification of parameters governing cell migratory processes, especially cell migratory processes in which cell-cell adhesion or repulsion are known to play a significant role.",
keywords = "Cell migration, adhesion, wound-healing, summary statistics, parameter identification, experimental design, approximate Bayesian computation, individual-based model, simulation",
author = "Robert Ross and Ruth Baker and Matthew Ford and Richard Mort and Christian Yates",
year = "2016",
month = aug,
day = "24",
doi = "10.1101/068791",
language = "English",
journal = "Biorxiv",
publisher = "Cold Spring Harbor Laboratory Press",

}

RIS

TY - JOUR

T1 - Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process

AU - Ross, Robert

AU - Baker, Ruth

AU - Ford, Matthew

AU - Mort, Richard

AU - Yates, Christian

PY - 2016/8/24

Y1 - 2016/8/24

N2 - 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 cell-cell interactions, such as adhesion and repulsion, have been shown to play an important role in cell migration. Initially, we demonstrate with a model of an ideal experiment that we are able to identify model parameters for agent motility and adhesion, given we choose appropriate summary statistics. Following this, we replace our model of an ideal experiment with a model representative of a practically realisable experiment. We demonstrate that, given the current (and commonly used) experimental set-up, model parameters cannot be accurately identified using approximate Bayesian computation methods. We compare new experimental designs through simulation, and show more accurate identification of model parameters is possible by expanding the size of the domain upon which the experiment is performed, as opposed to increasing the number of experimental repeats. The results presented in this work therefore describe time and cost-saving alterations for a commonly performed experiment for identifying cell motility parameters. Moreover, the results presented in this work will be of interest to those concerned with performing experiments that allow for the accurate identification of parameters governing cell migratory processes, especially cell migratory processes in which cell-cell adhesion or repulsion are known to play a significant role.

AB - 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 cell-cell interactions, such as adhesion and repulsion, have been shown to play an important role in cell migration. Initially, we demonstrate with a model of an ideal experiment that we are able to identify model parameters for agent motility and adhesion, given we choose appropriate summary statistics. Following this, we replace our model of an ideal experiment with a model representative of a practically realisable experiment. We demonstrate that, given the current (and commonly used) experimental set-up, model parameters cannot be accurately identified using approximate Bayesian computation methods. We compare new experimental designs through simulation, and show more accurate identification of model parameters is possible by expanding the size of the domain upon which the experiment is performed, as opposed to increasing the number of experimental repeats. The results presented in this work therefore describe time and cost-saving alterations for a commonly performed experiment for identifying cell motility parameters. Moreover, the results presented in this work will be of interest to those concerned with performing experiments that allow for the accurate identification of parameters governing cell migratory processes, especially cell migratory processes in which cell-cell adhesion or repulsion are known to play a significant role.

KW - Cell migration

KW - adhesion

KW - wound-healing

KW - summary statistics

KW - parameter identification

KW - experimental design

KW - approximate Bayesian computation

KW - individual-based model

KW - simulation

U2 - 10.1101/068791

DO - 10.1101/068791

M3 - Journal article

JO - Biorxiv

JF - Biorxiv

M1 - 068791

ER -