The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
High-throughput cellular microarray platforms: applications in drug discovery, toxicology and stem cell research
Open accessAbstract
Cellular microarrays are powerful experimental tools for high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput while reducing reagent consumption and the number of cells required, making these systems attractive for a wide range of assays in drug discovery, toxicology, stem cell research and potentially therapy. Here, we provide an overview of the emerging technologies that can be used to generate cellular microarrays, and we highlight recent significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies and promises to expedite drug discovery in the biotechnology and pharmaceutical industries.
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Cites
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Popova, A. A., Tronser, T., Demir, K., Haitz, P., Kuodyte, K., Starkuviene, V., Wajda, P., & Levkin, P. A. (2019) · Small · doi:10.1002/smll.201901299 · Cited by 84
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Metadata
- Authors
- Fernandes, T. G., Diogo, M. M., Clark, D. S., Dordick, J. S., & Cabral, J. M. S.
- Venue
- Trends in Biotechnology
- Publisher
- Elsevier BV
- Published
- 2009-06
- Volume
- 27
- Issue
- 6
- Pages
- 342-349
- ISSN
- 0167-7799 (ISSN-L)
- OpenAlex
- W2158361080
- Cited by
- 285
- References
- 67
- FWCI
- 1.32
- Type
- journal article
- Language
- en
- Open access
- green
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- Fernandes, T. G., Diogo, M. M., Clark, D. S., Dordick, J. S., & Cabral, J. M. S. (2009). High-throughput cellular microarray platforms: applications in drug discovery, toxicology and stem cell research. Trends in Biotechnology. https://doi.org/10.1016/j.tibtech.2009.02.009
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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.