Evidence map›Paper›PMID 20823849›Full record

ArticleMolecular systems biology2010

HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology.

Christoph Gille, Christian Bölling, Andreas Hoppe, Sascha Bulik, Sabrina Hoffmann, Katrin Hübner, Anja Karlstädt, Ramanan Ganeshan, Matthias König, Kristian Rother and 3 more

Abstract read
In one paragraph

Article in Molecular systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers.

0numbers the graph read from it
0cells of the map it votes in
139citing 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

139 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Longitudinal big biological data in the AI era.Molecular systems biology · 2025
    Review
  5. Review
  6. Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  7. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

79 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

13 authors.

Christoph GilleInstitute of Biochemistry, University Medicine Charité Berlin, Berlin, Germany.
Christian Bölling
Andreas Hoppe
Sascha Bulik
Sabrina Hoffmann
Katrin Hübner
Anja Karlstädt
Ramanan Ganeshan
Matthias König
Kristian Rother
Michael Weidlich
Jörn Behre
Herrmann-Georg Holzhütter

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present HepatoNet1, the first reconstruction of a comprehensive metabolic network of the human hepatocyte that is shown to accomplish a large canon of known metabolic liver functions. The network comprises 777 metabolites in six intracellular and two extracellular compartments and 2539 reactions, including 1466 transport reactions. It is based on the manual evaluation of >1500 original scientific research publications to warrant a high-quality evidence-based model. The final network is the result of an iterative process of data compilation and rigorous computational testing of network functionality by means of constraint-based modeling techniques. Taking the hepatic detoxification of ammonia as an example, we show how the availability of nutrients and oxygen may modulate the interplay of various metabolic pathways to allow an efficient response of the liver to perturbations of the homeostasis of blood compounds.

Indexed as

HepatocytesHumans

Identifiers

PMID20823849
PMCPMC2964118

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.