Evidence map›Paper›PMID 28088694›Full record

ReviewCurrent opinion in chemical biology2017

Metabolic network modeling with model organisms.

L Safak Yilmaz, Albertha Jm Walhout

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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  15. Review
  16. WormPaths:bioRxiv : the preprint server for biology · 2020
    Article
  17. Article
  18. Review
  19. Article
  20. Review
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.

L Safak YilmazProgram in Systems Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address: lutfu.yilmaz@umassmed.edu.
Albertha Jm WalhoutProgram in Systems Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address: marian.walhout@umassmed.edu.

Funding

Transcription networks in C elegans organogenesisR01DK068429 · NIDDK · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI A. J. Marian Walhout · 2005 to 2026
$10.9M
Identifying transcription factor binding sites in the C. elegans genomeR01GM082971 · NIGMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI WALHOUT, A. J. MARIAN · 2008 to 2016
$5.8M
Modeling of the metabolic network of Caenorhabditis elegansR21GM108045 · NIGMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI WALHOUT, A. J. MARIAN · 2015 to 2016
$461k
NIDDK NIH HHS R01 DK068429NIGMS NIH HHS R01 GM082971NIGMS NIH HHS R21 GM108045
6 · The paper itself

Abstract

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions.

Indexed as

GenomeModels, BiologicalAnimalsArabidopsisBacteriaEscherichia coliGene ExpressionHumansMetabolic Networks and PathwaysModels, AnimalPlantsSaccharomyces cerevisiae

Identifiers

PMID28088694
PMCPMC5458607

What OpenQuestion holds

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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.