Evidence map›Paper›PMID 39205165›Full record

ArticleViruses2024

VOGDB-Database of Virus Orthologous Groups.

Lovro Trgovec-Greif, Hans-Jörg Hellinger, Jean Mainguy, Alexander Pfundner, Dmitrij Frishman, Michael Kiening, Nicole Suzanne Webster, Patrick William Laffy, Michael Feichtinger, Thomas Rattei

Abstract read
In one paragraph

Article in Viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

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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

10 authors.

Lovro Trgovec-GreifCentre for Microbiology and Environmental Systems Science, University of Vienna, 1030 Vienna, Austria.ORCID 0000-0001-7795-0598
Hans-Jörg HellingerDoctoral School of Microbiology and Environmental Systems Science, University of Vienna, 1030 Vienna, Austria.ORCID 0000-0002-6119-3825
Jean MainguyGenoscope, 91000 Evry Cedex, France.ORCID 0009-0006-9160-9744
Alexander PfundnerCentre for Microbiology and Environmental Systems Science, University of Vienna, 1030 Vienna, Austria.ORCID 0000-0002-4171-8436
Dmitrij FrishmanDepartment of Bioinformatics, School of Life Sciences, Technical University Munich, 85350 Freising, Germany.
Michael KieningDepartment of Bioinformatics, School of Life Sciences, Technical University Munich, 85350 Freising, Germany.
Nicole Suzanne WebsterAustralian Institute of Marine Science, PMB no3 Townsville MC, Townsville 4810, Australia.ORCID 0000-0002-4753-5278
Patrick William LaffyAustralian Institute of Marine Science, PMB no3 Townsville MC, Townsville 4810, Australia.ORCID 0000-0002-6754-1691
Michael FeichtingerCentre for Microbiology and Environmental Systems Science, University of Vienna, 1030 Vienna, Austria.ORCID 0000-0003-0558-7552
Thomas RatteiCentre for Microbiology and Environmental Systems Science, University of Vienna, 1030 Vienna, Austria.ORCID 0000-0002-0592-7791

Funding

FWF Austrian Science Fund I1303Marie Skłodowska-Curie Actions Innovative Training Networks grant agreement 955974 (VIROINF)
6 · The paper itself

Abstract

Computational models of homologous protein groups are essential in sequence bioinformatics. Due to the diversity and rapid evolution of viruses, the grouping of protein sequences from virus genomes is particularly challenging. The low sequence similarities of homologous genes in viruses require specific approaches for sequence- and structure-based clustering. Furthermore, the annotation of virus genomes in public databases is not as consistent and up to date as for many cellular genomes. To tackle these problems, we have developed VOGDB, which is a database of virus orthologous groups. VOGDB is a multi-layer database that progressively groups viral genes into groups connected by increasingly remote similarity. The first layer is based on pair-wise sequence similarities, the second layer is based on the sequence profile alignments, and the third layer uses predicted protein structures to find the most remote similarity. VOGDB groups allow for more sensitive homology searches of novel genes and increase the chance of predicting annotations or inferring phylogeny. VOGD B uses all virus genomes from RefSeq and partially reannotates them. VOGDB is updated with every RefSeq release. The unique feature of VOGDB is the inclusion of both prokaryotic and eukaryotic viruses in the same clustering process, which makes it possible to explore old evolutionary relationships of the two groups. VOGDB is freely available at vogdb.org under the CC BY 4.0 license.

Indexed as

Computational BiologyGenome, ViralPhylogenyVirusesDatabases, GeneticViral ProteinsViral Proteinscomparative Genomicsgenome analysisgenome annotationorthologous groupsprotein familiesvirus genomes

Identifiers

PMID39205165
PMCPMC11360334

What OpenQuestion holds

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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.