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Cited by 419

The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.

Surgical Approaches to Create Murine Models of Human Wound Healing

Open access
Wong, Victor W., Sorkin, Michael, Glotzbach, Jason P., Longaker, Michael T., Gurtner, Geoffrey C.·2011·BioMed Research International

Abstract

Wound repair is a complex biologic process which becomes abnormal in numerous disease states. Although in vitro models have been important in identifying critical repair pathways in specific cell populations, in vivo models are necessary to obtain a more comprehensive and pertinent understanding of human wound healing. The laboratory mouse has long been the most common animal research tool and numerous transgenic strains and models have been developed to help researchers study the molecular pathways involved in wound repair and regeneration. This paper aims to highlight common surgical mouse models of cutaneous disease and to provide investigators with a better understanding of the benefits and limitations of these models for translational applications.

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Crossref · 10.1155/2011/969618

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Metadata

Authors
Wong, V. W., Sorkin, M., Glotzbach, J. P., Longaker, M. T., & Gurtner, G. C.
Venue
BioMed Research International
Publisher
Wiley
Published
2010-12
Volume
2011
Issue
1
Pages
969618-969618
ISSN
  • 1110-7243 (ISSN-L)
  • 2314-6133
  • 2314-6141
OpenAlex
W1963484569
Cited by
419
References
64
FWCI
12.12
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Surgical Approaches to Create Murine Models of Human Wound Healing. https://app.cochat.ai/papers/10.1155/2011/969618
The paper
Wong, V. W., Sorkin, M., Glotzbach, J. P., Longaker, M. T., & Gurtner, G. C. (2011). Surgical Approaches to Create Murine Models of Human Wound Healing. BioMed Research International. https://doi.org/10.1155/2011/969618

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.