Dataset Information

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.

ABSTRACT: Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate, ?. Estimating D and ? is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and ? have been proposed, these previous methods lead to point estimates of D and ?, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and ? using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and ? from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and ?. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and ?, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

SUBMITTER: Johnston ST

PROVIDER: S-EPMC4185435 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.

Johnston Stuart T ST Simpson Matthew J MJ McElwain D L Sean DL Binder Benjamin J BJ Ross Joshua V JV

Open biology 20140901 9

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate, λ. Estimating D and λ is imp ...[more]

PMID: 25209532

Similar Datasets

Project description:Population sex ratios are of high ecological relevance, but are challenging to determine in species lacking conspicuous external cues indicating their sex. Acoustic sexing is an option if vocalizations differ between sexes, but is precluded by overlapping distributions of the values of male and female vocalizations in many species. A method allowing the inference of sex ratios despite such an overlap will therefore greatly increase the information extractable from acoustic data. To meet this demand, we developed a novel approach using Approximate Bayesian Computation (ABC) to infer the sex ratio of populations from acoustic data. Additionally, parameters characterizing the male and female distribution of acoustic values (mean and standard deviation) are inferred. This information is then used to probabilistically assign a sex to a single acoustic signal. We furthermore develop a simpler means of sex ratio estimation based on the exclusion of calls from the overlap zone. Applying our methods to simulated data demonstrates that sex ratio and acoustic parameter characteristics of males and females are reliably inferred by the ABC approach. Applying both the ABC and the exclusion method to empirical datasets (echolocation calls recorded in colonies of lesser horseshoe bats, Rhinolophus hipposideros) provides similar sex ratios as molecular sexing. Our methods aim to facilitate evidence-based conservation, and to benefit scientists investigating ecological or conservation questions related to sex- or group specific behaviour across a wide range of organisms emitting acoustic signals. The developed methodology is non-invasive, low-cost and time-efficient, thus allowing the study of many sites and individuals. We provide an R-script for the easy application of the method and discuss potential future extensions and fields of applications. The script can be easily adapted to account for numerous biological systems by adjusting the type and number of groups to be distinguished (e.g. age, social rank, cryptic species) and the acoustic parameters investigated.

Dataset Information

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.

Publications

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets