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Transcriptomics
· 2022
Abstract
The field of transcriptomics has evolved substantially over the past few decades and has made remarkable contributions to toxicology and medicine. Mainly because of the discovery of high-throughput transcriptomics techniques such as microarray and RNA sequencing, it has become possible to determine the expression profile of the entire genome in a biological system. The gene expression data determined in a biological system in response to its exposure to xenobiotics may have implications for the prevention of toxicity and of the adverse health effects potentially associated with that exposure. Gene expression changes precede classical toxicity endpoints such as biochemical and histological changes in target organs and surrogate tissues. This has facilitated the identification of gene expression signatures as non-invasive or minimally invasive predictive biomarkers for the detection of early target organ toxicity. Similarly, bioinformatics analysis of the gene expression data provides valuable information regarding the mechanisms underlying the toxicity that results from exposure to xenobiotics in a biological system. As discussed in this chapter, global gene expression profiling has been employed in the identification of biomarkers for the early detection of toxicity, as well as for understanding the mechanisms involved in the toxicity. Similarly, non-invasive or minimally invasive biomarkers for the detection of diseases have been developed. After appropriate validations in human subjects, these findings may be employed to prevent the adverse health effects potentially associated with human exposure to toxic xenobiotics, as well as with diseases. disclaimer The findings and conclusions in this report are those of the author and do not necessarily represent the official position of the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention.
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Provenance
- Source
- OpenAlex
- DOI
- 10.1002/9781119807704.ch7
- Canonical
- link ↗
- Fetched
- 2026-10-15 MST
Cite this
APA
Joseph, P. (2022). Transcriptomics. https://doi.org/10.1002/9781119807704.ch7
Vancouver
Joseph P. Transcriptomics. 2022. doi:10.1002/9781119807704.ch7.
BibTeX
@article{pius2022Transc,
title = {Transcriptomics},
author = {Pius Joseph},
year = {2022},
doi = {10.1002/9781119807704.ch7},
}
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