A review on bioinformatics advances in CRISPR-Cas technology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Plant Science,Agronomy and Crop Science,Biotechnology
Link
https://link.springer.com/content/pdf/10.1007/s13562-022-00811-3.pdf
Reference120 articles.
1. Abadi S, Yan WX, Amar D, Mayrose I (2017) A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action. PLoS Comput Biol 13(10):e1005807. https://doi.org/10.1371/journal.pcbi.1005807
2. Abby SS, Néron B, Ménager H et al (2014) MacSyFinder: A program to mine genomes for molecular systems with an application to CRISPR-cas systems. PLoS ONE 9:e110726. https://doi.org/10.1371/JOURNAL.PONE.0110726
3. Agrotis A, Ketteler R (2015) A new age in functional genomics using CRISPR/Cas9 in arrayed library screening. Front Genet 6:300. https://doi.org/10.3389/fgene.2015.00300
4. Alkhnbashi OS, Shah SA, Garrett RA et al (2016) Characterizing leader sequences of CRISPR loci. Bioinformatics (Oxford, England) 32:i576–i585. https://doi.org/10.1093/BIOINFORMATICS/BTW454
5. Alkhnbashi OS, Meier T, Mitrofanov A, Backofen R, Voß B (2020) CRISPR-Cas bioinformatics. Methods 172:3–11. https://doi.org/10.1016/j.ymeth.2019.07.013
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