Systematic Functional Annotation and Visualization of Biological Networks
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Abstract
ABSTRACT Large-scale biological networks map functional connections between most genes in the genome and can potentially uncover high level organizing principles governing cellular functions. These networks, however, are famously complex and often regarded as disordered masses of tangled interactions (“hairballs”) that are nearly impenetrable to biologists. As a result, our current understanding of network functional organization is very limited. To address this problem, I developed a systematic quantitative approach for annotating biological networks and examining their functional structure. This method, named Spatial Analysis of Functional Enrichment (SAFE), detects network regions that are statistically overrepresented for a functional group or a quantitative phenotype of interest, and provides an intuitive visual representation of their relative positioning within the network. By successfully annotating the Saccharomyces cerevisiae genetic interaction network with Gene Ontology terms, SAFE proved to be sensitive to functional signals and robust to noise. In addition, SAFE annotated the network with chemical genomic data and uncovered a new potential mechanism of resistance to the anti-cancer drug bortezomib. Finally, SAFE showed that protein-protein interactions, despite their apparent complexity, also have a high level functional structure. These results demonstrate that SAFE is a powerful new tool for examining biological networks and advancing our understanding of the functional organization of the cell.
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- Authors
- Baryshnikova, A.
- Affiliations
- Princeton University (US)
- Corresponding author
- Baryshnikova, Anastasia
- Venue
- Cell Systems
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 2
- Issue
- 6
- Pages
- 412-421
- ISSN
- 2405-4712 (ISSN-L)
- OpenAlex
- W2949573120
- Cited by
- 148
- References
- 66
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 15 · 2023: 10 · 2022: 15 · 2021: 20 · 2020: 18 · 2019: 14 · 2018: 16 · 2017: 15 · 2016: 2
- FWCI
- 6.69
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell Systems (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Princeton University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- functional enrichment, network visualization, gene interaction networks, protein-protein interaction network, Gene Ontology, Saccharomyces cerevisiae, chemical genomics, vesicle trafficking, bortezomib resistance
- MeSH terms
- Algorithms, Models, Biological, Saccharomyces cerevisiae, Protein Interaction Mapping, Databases, Genetic, Gene Regulatory Networks, Molecular Sequence Annotation, Protein Interaction Maps, Gene Ontology
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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.
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