Evidence map›Paper›PMID 37098485›Full record

ArticleBMC bioinformatics2023

CRISPR-Cas-Docker: web-based in silico docking and machine learning-based classification of crRNAs with Cas proteins.

Ho-Min Park, Jongbum Won, Yunseol Park, Esla Timothy Anzaku, Joris Vankerschaver, Arnout Van Messem, Wesley De Neve, Hyunjin Shim

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In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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

8 authors.

Ho-Min ParkCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.ORCID http://orcid.org/0000-0001-9937-8617
Jongbum WonCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.
Yunseol ParkCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.ORCID http://orcid.org/0000-0002-2005-1847
Esla Timothy AnzakuCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.
Joris VankerschaverCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.ORCID http://orcid.org/0000-0002-5813-5659
Arnout Van MessemDepartment of Mathematics, University of Liège, 4000, Liège, Belgium.ORCID http://orcid.org/0000-0001-8545-7437
Wesley De NeveCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea.ORCID http://orcid.org/0000-0002-8190-3839
Hyunjin ShimCenter for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, 21985, South Korea. hyunjin.shim@ghent.ac.kr.ORCID http://orcid.org/0000-0002-7052-0971

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCRISPR-Cas-Docker is a web server for in silico docking experiments with CRISPR RNAs (crRNAs) and Cas proteins. This web server aims at providing experimentalists with the optimal crRNA-Cas pair predicted computationally when prokaryotic genomes have multiple CRISPR arrays and Cas systems, as frequently observed in metagenomic data.

resultsCRISPR-Cas-Docker provides two methods to predict the optimal Cas protein given a particular crRNA sequence: a structure-based method (in silico docking) and a sequence-based method (machine learning classification). For the structure-based method, users can either provide experimentally determined 3D structures of these macromolecules or use an integrated pipeline to generate 3D-predicted structures for in silico docking experiments.

conclusionCRISPR-Cas-Docker addresses the need of the CRISPR-Cas community to predict RNA-protein interactions in silico by optimizing multiple stages of computation and evaluation, specifically for CRISPR-Cas systems. CRISPR-Cas-Docker is available at www.crisprcasdocker.org as a web server, and at https://github.com/hshimlab/CRISPR-Cas-Docker as an open-source tool.

Indexed as

CRISPR-Cas SystemsRNAInternetRNACRISPR-Cas systemsCRISPR direct repeatIn silico dockingMachine learning-based classificationProtein tertiary structureRNA secondary structureRNA tertiary structure

Identifiers

PMID37098485
PMCPMC10127312

What OpenQuestion holds

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LicenceCC BY
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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.