Evidence map›Paper›PMID 25437607›Full record

ReviewPathogens (Basel, Switzerland)2014

Identifying pathogenicity islands in bacterial pathogenomics using computational approaches.

Dongsheng Che, Mohammad Shabbir Hasan, Bernard Chen

Open access · goldAbstract readReview
In one paragraph

Review in Pathogens (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

36 citing papers in PubMed, 88 citations in OpenAlex.

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  14. Coagulase-Negative Staphylococci Pathogenomics.International journal of molecular sciences · 2019
    Review
  15. Article
  16. Article
  17. Improved genomic island predictions with IslandPath-DIMOB.Bioinformatics (Oxford, England) · 2018
    Article
  18. Article
  19. Pathogenomics of Virulence Traits ofFrontiers in microbiology · 2018
    Article
  20. 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 3 institutions in 1 country.

Dongsheng CheDepartment of Computer Science, East Stroudsburg University of Pennsylvania, East Stroudsburg, PA 18301, USA. dche@po-box.esu.edu.
Mohammad Shabbir HasanDepartment of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. shabbir5@vt.edu.
Bernard ChenDepartment of Computer Science, University of Central Arkansas, Conway, AR 72035, USA. bchen@uca.edu.
East Stroudsburg University · USUniversity of Central Arkansas · USVirginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms.

Identifiers

PMID25437607
PMCPMC4235732
OpenAlexW2029034654

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.