Machine learning predicts new anti-CRISPR proteins
- Submitting institution
-
The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 12685
- Type
- D - Journal article
- DOI
-
10.1093/nar/gkaa219
- Title of journal
- Nucleic Acids Research
- Article number
- -
- First page
- 4698
- Volume
- 48
- Issue
- 9
- ISSN
- 1362-4962
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- 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
-
6
- Research group(s)
-
A - Applied Computing
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in a highly reputable journal, and with rapidly growing citations, this research is a culmination of a cross-disciplinary collaboration with Doudna and her lab (winner of the Nobel Prize in Chemistry 2020 and co-inventor of CRISPR-Cas technology). It reports the first machine learning guided discovery of novel anti-CRISPR proteins which can be used to control gene editing in cells, and has led to filing of a US patent application.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -