Evidence map›Paper›PMID 32455889›Full record

ArticleInternational journal of environmental research and public health2020

In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in

Farah Shahid, Usman Ali Ashfaq, Sania Saeed, Samman Munir, Ahmad Almatroudi, Mohsin Khurshid

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
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  9. Computational proteomics analysis ofFrontiers in plant science · 2024
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  10. BioMed research international · 2024
    Article
  11. Uncovering virulence factors inApplied and environmental microbiology · 2023
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Potential Therapeutic Candidates againstInternational journal of environmental research and public health · 2022
    Article
  17. Article
  18. Article
  19. Review
  20. In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors againstInternational journal of environmental research and public health · 2021
    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

6 authors at 2 institutions in 2 countries.

Farah ShahidDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan.
Usman Ali AshfaqDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan.
Sania SaeedDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan.
Samman MunirDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan.
Ahmad AlmatroudiDepartment of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 52571, Saudi Arabia.ORCID 0000-0002-1491-6402
Mohsin KhurshidDepartment of Microbiology, Government College University, Faisalabad, Punjab 38000, Pakistan.ORCID 0000-0002-3196-2857
Government College University, Faisalabad · PKQassim University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

ProteomicsStaphylococcal InfectionsStaphylococcus saprophyticusUrinary Tract InfectionsAgedComputational BiologyFemaleHumansMetabolic Networks and PathwaysPregnancybioinformaticsdrug targets identificationStaphylococcus saprophyticussubtractive proteomics

Identifiers

PMID32455889
PMCPMC7277342
OpenAlexW3026701861

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.