An updated evolutionary classification of CRISPR-Cas systems
- Submitting institution
-
University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1787
- Type
- D - Journal article
- DOI
-
10.1038/nrmicro3569
- Title of journal
- Nature Reviews Microbiology
- Article number
- -
- First page
- 722
- Volume
- 13
- Issue
- 11
- ISSN
- 1740-1526
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
https://www.nature.com/articles/nrmicro3569#article-info
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
20
- Research group(s)
-
-
- Citation count
- 993
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Here we introduce a computational approach to classify and characterize the adaptive immune system of archaea and bacteria (the CRISPR-cas loci) in an automated fashion with unprecedented accuracy. These results have been used and cited by thousands of researchers to gain deeper understanding on the variability of these systems, including by the Nobel Prize winner Jennifer Doudna in her 2016 Cell paper “Biology and applications of CRISPR systems” (10.1016/j.cell.2015.12.035). The applications derived by the better understanding of the CRISPR-cas system include precision genome regulation and interrogation which are currently employed in an increasing number of biomedical research and clinical studies.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -