Evidence map›Paper›PMID 30513931›Full record

ArticleViruses2018

The Challenges of Analysing Highly Diverse Picobirnavirus Sequence Data.

Matthew A Knox, Kristene R Gedye, David T S Hayman

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
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

12 citing papers in PubMed, 25 citations in OpenAlex.

  1. Picobirnavirus: how do you find where it's hiding?Critical reviews in microbiology · 2026
    Review
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  11. The True Host/s of Picobirnaviruses.Frontiers in veterinary science · 2020
    Review
  12. Article
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

3 authors at 1 institution in 1 country.

Matthew A KnoxMolecular Epidemiology and Public Health Laboratory (mEpiLab), Hopkirk Research Institute, Massey University, Private Bag 11-222, Palmerston North 4442, New Zealand. m.knox@massey.ac.nz.
Kristene R GedyeMolecular Epidemiology and Public Health Laboratory (mEpiLab), Hopkirk Research Institute, Massey University, Private Bag 11-222, Palmerston North 4442, New Zealand. K.Gedye@massey.ac.nz.
David T S HaymanMolecular Epidemiology and Public Health Laboratory (mEpiLab), Hopkirk Research Institute, Massey University, Private Bag 11-222, Palmerston North 4442, New Zealand. D.T.S.Hayman@massey.ac.nz.ORCID 0000-0003-0087-3015
Massey University · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The reliable identification and classification of infectious diseases is critical for understanding their biology and controlling their impact. Recent advances in sequencing technology have allowed insight into the remarkable diversity of the virosphere, of which a large component remains undiscovered. For these emerging or undescribed viruses, the process of classifying unknown sequences is heavily reliant on existing nucleotide sequence information in public databases. However, due to the enormous diversity of viruses, and past focus on the most prevalent and impactful virus types, databases are often incomplete. Picobirnaviridae is a dsRNA virus family with broad host and geographic range, but with relatively little sequence information in public databases. The family contains one genus,

Indexed as

Genetic VariationSequence Analysis, RNAFecesGenome, ViralPhylogenyPicobirnavirusRNA, Double-StrandedRNA, ViralRNA, Double-StrandedRNA, Viralphylogeneticspolymerase geneprotein structure homology-modellingRdRp geneviral dark matter

Identifiers

PMID30513931
PMCPMC6316005
OpenAlexW2902244453

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.