Evidence map›Paper›PMID 29616000›Full record

ArticleFrontiers in microbiology2018

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

Balachandran Manavalan, Tae H Shin, Gwang Lee

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 2 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

79 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  8. A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025
    Review
  9. Article
  10. Article
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  12. Recent Applications of Artificial Intelligence in Discovery of New Antibacterial Agents.Advances and applications in bioinformatics and chemistry : AABC · 2024
    Review
  13. Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Review
  14. Article
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  16. Article
  17. Review
  18. Article
  19. Article
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19 more citing papers are in PubMed but not listed here.

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.

Balachandran ManavalanDepartment of Physiology, Ajou University School of Medicine, Suwon, South Korea.
Tae H ShinDepartment of Physiology, Ajou University School of Medicine, Suwon, South Korea.
Gwang LeeDepartment of Physiology, Ajou University School of Medicine, Suwon, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to

Indexed as

bacteriophage virion proteinsfeature selectionhybrid featuresmachine learningsupport vector machine

Identifiers

PMID29616000
PMCPMC5864850

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.