Evidence map›Paper›PMID 23433509›Full record

ArticleBMC systems biology2013

Precise generation of systems biology models from KEGG pathways.

Clemens Wrzodek, Finja Büchel, Manuel Ruff, Andreas Dräger, Andreas Zell

Abstract read
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Article in BMC systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

31 citing papers in PubMed.

  1. Review
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  9. Finding MEMo: minimum sets of elementary flux modes.Journal of mathematical biology · 2019
    Article
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  15. Taking Bioinformatics to Systems Medicine.Methods in molecular biology (Clifton, N.J.) · 2016
    Review
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  17. Article
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  20. Comparison of human cell signaling pathway databases--evolution, drawbacks and challenges.Database : the journal of biological databases and curation · 2015
    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

5 authors.

Clemens WrzodekCenter for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de
Finja Büchel
Manuel Ruff
Andreas Dräger
Andreas Zell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe KEGG PATHWAY database provides a plethora of pathways for a diversity of organisms. All pathway components are directly linked to other KEGG databases, such as KEGG COMPOUND or KEGG REACTION. Therefore, the pathways can be extended with an enormous amount of information and provide a foundation for initial structural modeling approaches. As a drawback, KGML-formatted KEGG pathways are primarily designed for visualization purposes and often omit important details for the sake of a clear arrangement of its entries. Thus, a direct conversion into systems biology models would produce incomplete and erroneous models.

resultsHere, we present a precise method for processing and converting KEGG pathways into initial metabolic and signaling models encoded in the standardized community pathway formats SBML (Levels 2 and 3) and BioPAX (Levels 2 and 3). This method involves correcting invalid or incomplete KGML content, creating complete and valid stoichiometric reactions, translating relations to signaling models and augmenting the pathway content with various information, such as cross-references to Entrez Gene, OMIM, UniProt ChEBI, and many more.Finally, we compare several existing conversion tools for KEGG pathways and show that the conversion from KEGG to BioPAX does not involve a loss of information, whilst lossless translations to SBML can only be performed using SBML Level 3, including its recently proposed qualitative models and groups extension packages.

conclusionsBuilding correct BioPAX and SBML signaling models from the KEGG database is a unique characteristic of the proposed method. Further, there is no other approach that is able to appropriately construct metabolic models from KEGG pathways, including correct reactions with stoichiometry. The resulting initial models, which contain valid and comprehensive SBML or BioPAX code and a multitude of cross-references, lay the foundation to facilitate further modeling steps.

Indexed as

AlgorithmsDatabases, GeneticModels, BiologicalSoftwareProgramming LanguagesSignal TransductionSystems Biology

Identifiers

PMID23433509
PMCPMC3623889

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LicenceCC BY
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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.