ArticleOpen biology2014
Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.
Article in Open biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 65 citations in OpenAlex.
- An off-lattice discrete model to characterise filamentous yeast colony morphology.PLoS computational biology · 2024Article
- Model-based inference of a dual role for HOPS in regulating guard cell vacuole fusion.In silico plants · 2024Article
- Model-based inference of a plant-specific dual role for HOPS in regulating guard cell vacuole fusion.bioRxiv : the preprint server for biology · 2023Article
- FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes.Bioinformatics (Oxford, England) · 2023Article
- A noble extended stochastic logistic model for cell proliferation with density-dependent parameters.Scientific reports · 2022Article
- Mathematical Modeling Can Advance Wound Healing Research.Advances in wound care · 2021Review
- Detection and characterization of chemotaxis without cell tracking.Journal of the Royal Society, Interface · 2021Article
- Predicting population extinction in lattice-based birth-death-movement models.Proceedings. Mathematical, physical, and engineering sciences · 2020Article
- Identifying density-dependent interactions in collective cell behaviour.Journal of the Royal Society, Interface · 2020Article
- Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art.Journal of the Royal Society, Interface · 2019Article
- The impact of experimental design choices on parameter inference for models of growing cell colonies.Royal Society open science · 2018Article
- Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis.Journal of mathematical biology · 2018Article
- Quantifying the dominant growth mechanisms of dimorphic yeast using a lattice-based model.Journal of the Royal Society, Interface · 2017Article
- Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process.NPJ systems biology and applications · 2017Article
- Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functions.Journal of the Royal Society, Interface · 2016Article
- Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model.BMC systems biology · 2015Article
- Spatial moment dynamics for collective cell movement incorporating a neighbour-dependent directional bias.Journal of the Royal Society, Interface · 2015Article
- Spectral analysis of pair-correlation bandwidth: application to cell biology images.Royal Society open science · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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, λ. Estimating D and λ 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 λ have been proposed, these previous methods lead to point estimates of D and λ, 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 λ using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and λ 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 λ. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and λ, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.