The DOI matches its Crossref record; 134 of the 134 references it cites were found in a registry or an index.
The pig as an animal model for human pathologies: A proteomics perspective
Abstract
Traditional biomedical models are easy to manage in experimental facilities and allow fast and affordable basic genetic studies related to human disorders, but in some cases they do not always represent the complexity of their physiology. Translational medicine demands selected models depending on the particularities of the human disease to be investigated, reproducing as closely as possible the evolution, clinical symptoms and molecular pathways, cells or tissues involved in the dysfunction. Thus, pig models offer an alternative because of their anatomical and physiological similarities to humans and the availability of genomic, transcriptomic and, progressively more, proteomic tools for analysis of this species. Furthermore, there is a wide range of natural, selected and transgenic porcine breeds. The present review provides a summary of the applications of the pig as a model for metabolic, cardiovascular, infectious diseases, xenotransplantation and neurological disorders and an overview of the possibilities that the diverse proteomic techniques offer to study these pathologies in depth.
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Metadata
- Authors
- Bassols, A., Costa, C., Eckersall, P. D., Osada, J., Sabrià, J., & Tibau, J.
- Venue
- PROTEOMICS – Clinical Applications
- Publisher
- Wiley
- Published
- 2014-10
- Volume
- 8
- Issue
- 9-10
- Pages
- 715-731
- ISSN
- 1862-8346 (ISSN-L)
- 1862-8354
- OpenAlex
- W2013606469
- Cited by
- 254
- References
- 134
- FWCI
- 10.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bassols, A., Costa, C., Eckersall, P. D., Osada, J., Sabrià, J., & Tibau, J. (2014). The pig as an animal model for human pathologies: A proteomics perspective. PROTEOMICS – Clinical Applications. https://doi.org/10.1002/prca.201300099
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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.