Evidence map›Paper›PMID 30871454›Full record

ArticleBMC bioinformatics2019

PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome.

Kanwal Naz, Anam Naz, Shifa Tariq Ashraf, Muhammad Rizwan, Jamil Ahmad, Jan Baumbach, Amjad Ali

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

57 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Design of a Novel Peptide-Based Vaccine TargetingInternational journal of dentistry · 2026
    Article
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  11. Review
  12. Article
  13. Article
  14. Review
  15. Average Nucleotide Identity basedbioRxiv : the preprint server for biology · 2024
    Article
  16. Frontiers in immunology · 2024
    Review
  17. Article
  18. Article
  19. Article
  20. Proteome level analysis of drug-resistantFrontiers in microbiology · 2023
    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

7 authors.

Kanwal NazAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan.
Anam NazAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan.
Shifa Tariq AshrafAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan.
Muhammad RizwanResearch Center for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan.
Jamil AhmadResearch Center for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan.
Jan BaumbachChair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munchen, Germany.
Amjad AliAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan. amjaduni@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA revolutionary diversion from classical vaccinology to reverse vaccinology approach has been observed in the last decade. The ever-increasing genomic and proteomic data has greatly facilitated the vaccine designing and development process. Reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome. To look for broad-spectrum immunogenic targets and analysis of closely-related bacterial species, the assimilation of pangenome concept into reverse vaccinology approach is essential. The categories of species pangenome such as core, accessory, and unique genes sets can be analyzed for the identification of vaccine candidates through reverse vaccinology.

resultsWe have designed an integrative computational pipeline term as "PanRV" that employs both the pangenome and reverse vaccinology approaches. PanRV comprises of four functional modules including i) Pangenome Estimation Module (PGM) ii) Reverse Vaccinology Module (RVM) iii) Functional Annotation Module (FAM) and iv) Antibiotic Resistance Association Module (ARM). The pipeline is tested by using genomic data from 301 genomes of Staphylococcus aureus and the results are verified by experimentally known antigenic data.

conclusionThe proposed pipeline has proved to be the first comprehensive automated pipeline that can precisely identify putative vaccine candidates exploiting the microbial pangenome. PanRV is a Linux based package developed in JAVA language. An executable installer is provided for ease of installation along with a user manual at https://sourceforge.net/projects/panrv2/ .

Indexed as

Bacterial VaccinesGenomicsHumansProteomicsVaccinologyBacterial VaccinesAnd therapeutic targetsCore genomeMicrobial speciesPangenomePanRVReverse vaccinologyVaccine targets

Identifiers

PMID30871454
PMCPMC6419457

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.