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

BioRxiv : the Preprint Server for Biology
Robert RossChristian Yates

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 presente...Continue Reading

Related Concepts

Tissue Adhesions
Cell Communication
Cell Motility
Experimental Design
Size
Simulation
Research Study
Pharmacologic Substance
Computed (Procedure)
Transcriptional Activation Domain

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