The DOI matches its OpenAlex record; 3 of the 3 references it cites were found in a registry or an index.
Laser capture microdissection: Big data from small samples.
Open accessAbstract
Any tissue is made up of a heterogeneous mix of spatially distributed cell types. In response to any (patho) physiological cue, responses of each cell type in any given tissue may be unique and cannot be homogenized across cell-types and spatial co-ordinates. For example, in response to myocardial infarction, on one hand myocytes and fibroblasts of the heart tissue respond differently. On the other hand, myocytes in the infarct core respond differently compared to those in the peri-infarct zone. Therefore, isolation of pure targeted cells is an important and essential step for the molecular analysis of cells involved in the progression of disease. Laser capture microdissection (LCM) is powerful to obtain a pure targeted cell subgroup, or even a single cell, quickly and precisely under the microscope, successfully tackling the problem of tissue heterogeneity in molecular analysis. This review presents an overview of LCM technology, the principles, advantages and limitations and its down-stream applications in the fields of proteomics, genomics and transcriptomics. With powerful technologies and appropriate applications, this technique provides unprecedented insights into cell biology from cells grown in their natural tissue habitat as opposed to those cultured in artificial petri dish conditions.
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Cites
The sequence of the human genome
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Mixed‐species biofilm compromises wound healing by disrupting epidermal barrier function
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“Recently, we have also shown the use of LCM in capturing biofilms from porcine wounds, allowing for transcriptomic analysis of biofilms being performed (Roy et al., 2014).”
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Cited by
RNA sequencing: the teenage years
Stark, R., Grzelak, M., & Hadfield, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0150-2 · Cited by 1,915
Eleven grand challenges in single-cell data science
Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1926-6 · Cited by 1,327
Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing
Casasent, A. K., Schalck, A., Gao, R., Sei, E., Long, A., Pangburn, W., Casasent, T., Meric-Bernstam, F., Edgerton, M. E., & Navin, N. E. (2018) · Cell · doi:10.1016/j.cell.2017.12.007 · Cited by 411
Wilpiszeski, R. L., Aufrecht, J. A., Retterer, S. T., Sullivan, M. B., Graham, D. E., Pierce, E. M., Zablocki, O. D., Palumbo, A. V., & Elias, D. A. (2019) · Applied and Environmental Microbiology · doi:10.1128/aem.00324-19 · Cited by 441
Single Cell Isolation and Analysis
Hu, P., Zhang, W., Xin, H., & Deng, G. (2016) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2016.00116 · Cited by 384
Metadata
- Authors
- Datta, S., Malhotra, L., Dickerson, R. M., Chaffee, S. M., Sen, C. K., & Roy, S.
- Venue
- PubMed
- Publisher
- National Institutes of Health
- Published
- 2015-11-01
- Volume
- 30
- Issue
- 11
- Pages
- 1255-69
- OpenAlex
- W255464861
- Cited by
- 232
- References
- 3
- FWCI
- 9.13
- Type
- journal article
- Language
- en
- Open access
- green
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- Datta, S., Malhotra, L., Dickerson, R. M., Chaffee, S. M., Sen, C. K., & Roy, S. (2015). Laser capture microdissection: Big data from small samples. PubMed. https://doi.org/10.14670/hh-11-622
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