Evidence map›Paper›PMID 19888215›Full record

ReviewMolecular systems biology2009

Applications of genome-scale metabolic reconstructions.

Matthew A Oberhardt, Bernhard Ø Palsson, Jason A Papin

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 391 papers.

0numbers the graph read from it
0cells of the map it votes in
391citing 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

391 citing papers in PubMed.

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  10. Longitudinal big biological data in the AI era.Molecular systems biology · 2025
    Review
  11. Article
  12. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Genome-scale model ofMicrobiology spectrum · 2024
    Article

331 more citing papers are in PubMed but not listed here.

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.

Matthew A OberhardtDepartment of Biomedical Engineering, University of Virginia, Health System, Charlottesville, VA, USA.
Bernhard Ø Palsson
Jason A Papin

Funding

BIOTECHNOLOGY TRAINING PROGRAMT32GM008715 · NIGMS · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI LAURIE, GORDON WILLIAM · 2000 to 2019
$6.6M
NIGMS NIH HHS GM08715NIGMS NIH HHS T32 GM008715
6 · The paper itself

Abstract

The availability and utility of genome-scale metabolic reconstructions have exploded since the first genome-scale reconstruction was published a decade ago. Reconstructions have now been built for a wide variety of organisms, and have been used toward five major ends: (1) contextualization of high-throughput data, (2) guidance of metabolic engineering, (3) directing hypothesis-driven discovery, (4) interrogation of multi-species relationships, and (5) network property discovery. In this review, we examine the many uses and future directions of genome-scale metabolic reconstructions, and we highlight trends and opportunities in the field that will make the greatest impact on many fields of biology.

Indexed as

Models, GeneticBiological EvolutionGenetic EngineeringGenomeMetabolic Networks and Pathways

Identifiers

PMID19888215
PMCPMC2795471

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.