Evidence map›Paper›PMID 33251208›Full record

ReviewFrontiers in cell and developmental biology2020

Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens.

Mustafa Sertbas, Kutlu O Ulgen

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

24 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
  2. Article
  3. Dynamic metabolic modelling of ATP allocation during viral infection.Journal of the Royal Society, Interface · 2026
    Article
  4. Frontiers in bioinformatics · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Genome-scale model ofMicrobiology spectrum · 2024
    Article
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  14. Review
  15. Article
  16. Article
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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

2 authors at 2 institutions in 1 country.

Mustafa SertbasDepartment of Chemical Engineering, Bogazici University, Istanbul, Turkey.
Kutlu O UlgenDepartment of Chemical Engineering, Bogazici University, Istanbul, Turkey.
Boğaziçi University · TRIstanbul Technical University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogens give rise to a wide range of diseases threatening global health and hence drawing public health agencies' attention to establish preventative and curative solutions. Genome-scale metabolic modeling is ever increasingly used tool for biomedical applications including the elucidation of antibiotic resistance, virulence, single pathogen mechanisms and pathogen-host interaction systems. With this approach, the sophisticated cellular system of metabolic reactions inside the pathogens as well as between pathogen and host cells are represented in conjunction with their corresponding genes and enzymes. Along with essential metabolic reactions, alternate pathways and fluxes are predicted by performing computational flux analyses for the growth of pathogens in a very short time. The genes or enzymes responsible for the essential metabolic reactions in pathogen growth are regarded as potential drug targets, as

Indexed as

flux balance analysis (FBA)flux variability analysisgene essentialitygenome-scale metabolic modelsinfectionpathogenpathogen-host interactionssystems biology

Identifiers

PMID33251208
PMCPMC7673413
OpenAlexW3096881113

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.