Evidence map›Paper›PMID 19144179›Full record

ArticleBMC systems biology2009

Reconstruction and logical modeling of glucose repression signaling pathways in Saccharomyces cerevisiae.

Tobias S Christensen, Ana Paula Oliveira, Jens Nielsen

Abstract read
In one paragraph

Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Construction of a globally modular recombinantSynthetic and systems biotechnology · 2026
    Article
  2. Engineering a universal and efficient platform for terpenoid synthesis in yeast.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  3. Article
  4. Heuristic shortest hyperpaths in cell signaling hypergraphs.Algorithms for molecular biology : AMB · 2022
    Article
  5. Review
  6. D-Xylose Sensing inInternational journal of molecular sciences · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Signaling hypergraphs.Trends in biotechnology · 2014
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Hypergraphs and cellular networks.PLoS computational biology · 2009
    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.

Tobias S ChristensenCenter for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. tschri@mit.edu
Ana Paula Oliveira
Jens Nielsen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the yeast Saccharomyces cerevisiae, the presence of high levels of glucose leads to an array of down-regulatory effects known as glucose repression. This process is complex due to the presence of feedback loops and crosstalk between different pathways, complicating the use of intuitive approaches to analyze the system.

resultsWe established a logical model of yeast glucose repression, formalized as a hypergraph. The model was constructed based on verified regulatory interactions and it includes 50 gene transcripts, 22 proteins, 5 metabolites and 118 hyperedges. We computed the logical steady states of all nodes in the network in order to simulate wildtype and deletion mutant responses to different sugar availabilities. Evaluation of the model predictive power was achieved by comparing changes in the logical state of gene nodes with transcriptome data. Overall, we observed 71% true predictions, and analyzed sources of errors and discrepancies for the remaining.

conclusionThough the binary nature of logical (Boolean) models entails inherent limitations, our model constitutes a primary tool for storing regulatory knowledge, searching for incoherencies in hypotheses and evaluating the effect of deleting regulatory elements involved in glucose repression.

Indexed as

Models, BiologicalGlucoseMetabolic Networks and PathwaysRepressor ProteinsSaccharomyces cerevisiaeSignal TransductionGlucoseRepressor Proteins

Identifiers

PMID19144179
PMCPMC2661888

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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.