The DOI matches its Crossref record; 57 of the 58 references it cites were found in a registry or an index.
A gene ontology inferred from molecular networks
Open accessAbstract
Ontologies have proven very useful for capturing knowledge as a hierarchy of terms and their interrelationships. In biology a major challenge has been to construct ontologies of gene function given incomplete biological knowledge and inconsistencies in how this knowledge is manually curated. Here we show that large networks of gene and protein interactions in Saccharomyces cerevisiae can be used to infer an ontology whose coverage and power are equivalent to those of the manually curated Gene Ontology (GO). The network-extracted ontology (NeXO) contains 4,123 biological terms and 5,766 term-term relations, capturing 58% of known cellular components. We also explore robust NeXO terms and term relations that were initially not cataloged in GO, a number of which have now been added based on our analysis. Using quantitative genetic interaction profiling and chemogenomics, we find further support for many of the uncharacterized terms identified by NeXO, including multisubunit structures related to protein trafficking or mitochondrial function. This work enables a shift from using ontologies to evaluate data to using data to construct and evaluate ontologies.
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“As observed previously (16), this indicates that novel functional organization is embedded within large-scale, unbiased datasets, which may not be captured completely by functional standards, including GO as it is currently organized (14).”
From A global genetic interaction network maps a wiring diagram of cellular function (2016) · cites this paper as [16]
In the citing paper
“The community detection approach was well illustrated in recent analyses of protein-protein interaction networks in yeast (Dutkowski et al., 2013) and human (Huttlin et al., 2015).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Dutkowski et al., 2013
In the citing paper
“For instance, the multiscale models of cellular components constructed by the NeXO and Mashup efforts (see above) found that the majority of cellular components catalogued in GO could be recovered from hierarchical detection of communities in protein network data (Cho et al., 2016; Dutkowski et al., 2013).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Dutkowski et al., 2013
In the citing paper
“Conversely, hierarchical maps generated from proximity networks can be thought of as a type of ontology, as demonstrated in the NeXO project (Dutkowski et al., 2013), albeit one that is driven by direct data analysis rather than manual curation of literature.”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Dutkowski et al., 2013
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Metadata
- Authors
- Dutkowski, J., Kramer, M., Surma, M. A., Balakrishnan, R., Cherry, J. M., Krogan, N. J., & Ideker, T.
- Affiliations
- University of California San Diego (US)
- Stanford University (US)
- Gladstone Institutes (US)
- Corresponding author
- Dutkowski, Janusz
- Ideker, Trey
- Venue
- Nature Biotechnology
- Published
- 2012-12-16
- Volume
- 31
- Issue
- 1
- Pages
- 38-45
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC3654867
- OpenAlex
- W2143962926
- Cited by
- 184
- References
- 58
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 3 · 2023: 4 · 2022: 7 · 2021: 23 · 2020: 12 · 2019: 15 · 2018: 21 · 2017: 23 · 2016: 18 · 2015: 18 · 2014: 17 · 2013: 15
- FWCI
- 6.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (GM085764, GM 103504, GM081879)
- National Human Genome Research Institute (U41HG002273)
- National Institute of General Medical Sciences (R01GM084448, P50GM081879, P50GM085764, P41GM103504, T32GM007198)
- National Institute of Allergy and Infectious Diseases (P30AI027763)
- National Institute of Environmental Health Sciences (R01ES014811)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- Gene Ontology, nEXO, protein-protein interaction network, gene interaction networks, Saccharomyces cerevisiae, term relations, chemogenomics, protein trafficking, mitochondrial function, multi-subunit protein complexes
- MeSH terms
- Fungal Proteins, Genes, Fungal, Saccharomyces cerevisiae, Gene Regulatory Networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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