Evidence map›Paper›PMID 34133710›Full record

ArticleNucleic acids research2021

CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems.

Omer S Alkhnbashi, Alexander Mitrofanov, Robson Bonidia, Martin Raden, Van Dinh Tran, Florian Eggenhofer, Shiraz A Shah, Ekrem Öztürk, Victor A Padilha, Danilo S Sanches and 2 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. Review
  3. New Insights into CRISPR-like Arrays inPathogens (Basel, Switzerland) · 2026
    Article
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  5. Article
  6. Review
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Omer S AlkhnbashiBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0001-8088-590X
Alexander MitrofanovBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
Robson BonidiaInstitute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, SP, Brazil.
Martin RadenBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0002-7926-5911
Van Dinh TranBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0002-7357-4959
Florian EggenhoferBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0001-9564-7525
Shiraz A ShahCopenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Denmark.
Ekrem ÖztürkBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
Victor A PadilhaInstitute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, SP, Brazil.
Danilo S SanchesUniversidade Tecnológica Federal do Paraná, Campus Cornélio Procópio, 86300000 Cornélio Procópio, PR, Brazil.
André C P L F de CarvalhoInstitute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, SP, Brazil.
Rolf BackofenBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0001-8231-3323

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CRISPR-Cas systems are adaptive immune systems in prokaryotes, providing resistance against invading viruses and plasmids. The identification of CRISPR loci is currently a non-standardized, ambiguous process, requiring the manual combination of multiple tools, where existing tools detect only parts of the CRISPR-systems, and lack quality control, annotation and assessment capabilities of the detected CRISPR loci. Our CRISPRloci server provides the first resource for the prediction and assessment of all possible CRISPR loci. The server integrates a series of advanced Machine Learning tools within a seamless web interface featuring: (i) prediction of all CRISPR arrays in the correct orientation; (ii) definition of CRISPR leaders for each locus; and (iii) annotation of cas genes and their unambiguous classification. As a result, CRISPRloci is able to accurately determine the CRISPR array and associated information, such as: the Cas subtypes; cassette boundaries; accuracy of the repeat structure, orientation and leader sequence; virus-host interactions; self-targeting; as well as the annotation of cas genes, all of which have been missing from existing tools. This annotation is presented in an interactive interface, making it easy for scientists to gain an overview of the CRISPR system in their organism of interest. Predictions are also rendered in GFF format, enabling in-depth genome browser inspection. In summary, CRISPRloci constitutes a full suite for CRISPR-Cas system characterization that offers annotation quality previously available only after manual inspection.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsMolecular Sequence AnnotationSoftwareCRISPR-Associated ProteinsMachine LearningCRISPR-Associated Proteins

Identifiers

PMID34133710
PMCPMC8265192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.