Cargando…
CRISPRcasIdentifier: Machine learning for accurate identification and classification of CRISPR-Cas systems
BACKGROUND: CRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas systems is no longer viable. Thus, an automated approach is required fo...
Autores principales: | Padilha, Victor A, Alkhnbashi, Omer S, Shah, Shiraz A, de Carvalho, André C P L F, Backofen, Rolf |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298778/ https://www.ncbi.nlm.nih.gov/pubmed/32556168 http://dx.doi.org/10.1093/gigascience/giaa062 |
Ejemplares similares
-
CRISPRloci: comprehensive and accurate annotation of CRISPR–Cas systems
por: Alkhnbashi, Omer S, et al.
Publicado: (2021) -
Casboundary: automated definition of integral Cas cassettes
por: Padilha, Victor A, et al.
Publicado: (2020) -
Comprehensive search for accessory proteins encoded with archaeal and bacterial type III CRISPR-cas gene cassettes reveals 39 new cas gene families
por: Shah, Shiraz A., et al.
Publicado: (2018) -
StoatyDive: Evaluation and classification of peak profiles for sequencing data
por: Heyl, Florian, et al.
Publicado: (2021) -
CRISPRstrand: predicting repeat orientations to determine the crRNA-encoding strand at CRISPR loci
por: Alkhnbashi, Omer S., et al.
Publicado: (2014)