Condition-specific series of metabolic sub-networks and its application for gene set enrichment analysis Article Swipe
Van Du T. Tran
,
Sébastien Moretti
,
Alix T. Coste
,
Sara Amorim-Vaz
,
Dominique Sanglard
,
Marco Pagni
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/bty929
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/bty929
Motivation Genome-scale metabolic networks and transcriptomic data represent complementary sources of knowledge about an organism’s metabolism, yet their integration to achieve biological insight remains challenging. Results We investigate here condition-specific series of metabolic sub-networks constructed by successively removing genes from a comprehensive network. The optimal order of gene removal is deduced from transcriptomic data. The sub-networks are evaluated via a fitness function, which estimates their degree of alteration. We then consider how a gene set, i.e. a group of genes contributing to a common biological function, is depleted in different series of sub-networks to detect the difference between experimental conditions. The method, named metaboGSE, is validated on public data for Yarrowia lipolytica and mouse. It is shown to produce GO terms of higher specificity compared to popular gene set enrichment methods like GSEA or topGO. Availability and implementation The metaboGSE R package is available at https://CRAN.R-project.org/package=metaboGSE. Supplementary information Supplementary data are available at Bioinformatics online.
Related Topics
Concepts
Yarrowia
Metabolic network
Set (abstract data type)
Function (biology)
Computational biology
Computer science
Gene
Transcriptome
R package
Gene regulatory network
Genome
Organism
Series (stratigraphy)
Data mining
Biology
Genetics
Gene expression
Computational science
Programming language
Paleontology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/bioinformatics/bty929
- https://academic.oup.com/bioinformatics/article-pdf/35/13/2258/28878310/bty929.pdf
- OA Status
- hybrid
- Cited By
- 14
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2952894564
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2952894564Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/bioinformatics/bty929Digital Object Identifier
- Title
-
Condition-specific series of metabolic sub-networks and its application for gene set enrichment analysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-11-15Full publication date if available
- Authors
-
Van Du T. Tran, Sébastien Moretti, Alix T. Coste, Sara Amorim-Vaz, Dominique Sanglard, Marco PagniList of authors in order
- Landing page
-
https://doi.org/10.1093/bioinformatics/bty929Publisher landing page
- PDF URL
-
https://academic.oup.com/bioinformatics/article-pdf/35/13/2258/28878310/bty929.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/bioinformatics/article-pdf/35/13/2258/28878310/bty929.pdfDirect OA link when available
- Concepts
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Yarrowia, Metabolic network, Set (abstract data type), Function (biology), Computational biology, Computer science, Gene, Transcriptome, R package, Gene regulatory network, Genome, Organism, Series (stratigraphy), Data mining, Biology, Genetics, Gene expression, Computational science, Programming language, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
14Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2023: 2, 2022: 2, 2021: 4, 2020: 4Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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