The DOI matches its Crossref record.
Wound-Healing Assay
Abstract
The wound-healing assay is simple, inexpensive, and one of the earliest developed methods to study directional cell migration in vitro. This method mimics cell migration during wound healing in vivo. The basic steps involve creating a "wound" in a cell monolayer, capturing the images at the beginning and at regular intervals during cell migration to close the wound, and comparing the images to quantify the migration rate of the cells. It is particularly suitable for studies on the effects of cell-matrix and cell-cell interactions on cell migration. A variation of this method that tracks the migration of individual cells in the leading edge of the wound is also described in this chapter.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
In vitro cell migration and invasion assays
Kramer, N., Walzl, A., Unger, C., Rosner, M., Krupitza, G., Hengstschläger, M., & Dolznig, H. (2013) · Mutation Research/Reviews in Mutation Research · doi:10.1016/j.mrrev.2012.08.001 · Cited by 1,170
An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays
(2020) · doi:10.1371/journal.pone.0232565 · Cited by 851
Bielas, S. L., Silhavy, J. L., Brancati, F., Kisseleva, M. V., Al-Gazali, L., Sztriha, L., Bayoumi, R. A., Zaki, M. S., Abdel-Aleem, A., Rosti, R. O., et al. (2009) · Nature Genetics · doi:10.1038/ng.423 · Cited by 396
Shen, T.-L., Park, A. Y.-J., Alcaraz, A., Peng, X., Jang, I., Koni, P., Flavell, R. A., Gu, H., & Guan, J.-L. (2005) · The Journal of Cell Biology · doi:10.1083/jcb.200411155 · Cited by 304
Self-citationNF-kappaB Is Involved in the Regulation of EMT Genes in Breast Cancer Cells
Pires, B. R. B., Mencalha, A. L., Ferreira, G. M., de Souza, W. F., Morgado-Díaz, J. A., Maia, A. M., Corrêa, S., & Abdelhay, E. S. F. W. (2017) · PLOS ONE · doi:10.1371/journal.pone.0169622 · Cited by 296
Metadata
- Authors
- Rodriguez, L. G., Wu, X., & Guan, J.-L.
- Venue
- Cell Migration
- Publisher
- Humana Press
- Published
- 2004-12-01
- Volume
- 294
- Pages
- 023-030
- OpenAlex
- W2201991444
- Cited by
- 557
- References
- 0
- FWCI
- 6.89
- Type
- book chapter
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Wound-Healing Assay. https://app.cochat.ai/papers/10.1385/1-59259-860-9:023
- The paper
- Rodriguez, L. G., Wu, X., & Guan, J.-L. (2004). Wound-Healing Assay. Cell Migration. https://doi.org/10.1385/1-59259-860-9%3A023
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.