@article{huang_yang_yi_asif_wang_lithgow_zhang_minhas_yin_2020, 
  title={AcrDB: a database of anti-CRISPR operons in prokaryotes and viruses}, 
  DOI={10.1093/nar/gkaa857}, 
  abstractNote={<jats:title>Abstract</jats:title>
               <jats:p>CRISPR–Cas is an anti-viral mechanism of prokaryotes that has been widely adopted for genome editing. To make CRISPR–Cas genome editing more controllable and safer to use, anti-CRISPR proteins have been recently exploited to prevent excessive/prolonged Cas nuclease cleavage. Anti-CRISPR (Acr) proteins are encoded by (pro)phages/(pro)viruses, and have the ability to inhibit their host's CRISPR–Cas systems. We have built an online database AcrDB (http://bcb.unl.edu/AcrDB) by scanning ∼19 000 genomes of prokaryotes and viruses with AcrFinder, a recently developed Acr-Aca (Acr-associated regulator) operon prediction program. Proteins in Acr-Aca operons were further processed by two machine learning-based programs (AcRanker and PaCRISPR) to obtain numerical scores/ranks. Compared to other anti-CRISPR databases, AcrDB has the following unique features: (i) It is a genome-scale database with the largest collection of data (39 799 Acr-Aca operons containing Aca or Acr homologs); (ii) It offers a user-friendly web interface with various functions for browsing, graphically viewing, searching, and batch downloading Acr-Aca operons; (iii) It focuses on the genomic context of Acr and Aca candidates instead of individual Acr protein family and (iv) It collects data with three independent programs each having a unique data mining algorithm for cross validation. AcrDB will be a valuable resource to the anti-CRISPR research community.</jats:p>}, 
  publisher={Oxford University Press (OUP)}, 
  author={Huang, Le and Yang, Bowen and Yi, Haidong and Asif, Amina and Wang, Jiawei and Lithgow, Trevor and Zhang, Han and Minhas, Fayyaz ul Amir Afsar and Yin, Yanbin}, 
  year={2020}, 
  month={Oct}
  }