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Updated: May 19, 2026
08:38
Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
Published on: March 3, 2015
FACETS: multi-faceted functional decomposition of protein interaction networks
Boon-Siew Seah1, Sourav S Bhowmick, C Forbes Dewey
1School of Computer Engineering, Nanyang Technological University, Singapore. seah0097@ntu.edu.sg
Bioinformatics (Oxford, England)
|August 22, 2012
Summary
FACETS is a novel algorithm that decomposes protein-protein interaction (PPI) networks using Gene Ontology (GO) annotations. It provides a multi-faceted atlas of functional decompositions for better understanding of complex biological networks.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Large-scale protein-protein interaction (PPI) datasets enable network analysis.
- High-throughput PPI data analysis presents challenges due to data volume.
- Gene Ontology (GO) annotations offer a framework for functional interpretation.
Purpose of the Study:
- To develop a novel algorithm, FACETS, for PPI network decomposition.
- To address the challenge of analyzing large-scale PPI data.
- To generate a multi-faceted atlas of functional decompositions for PPI networks.
Main Methods:
- Proposed a novel PPI network decomposition algorithm named FACETS.
- Utilized Gene Ontology (GO) annotations for functional interpretation.
- Optimized inter-facet orthogonality and intra-facet cluster modularity for interpretative value.
Main Results:
- Tested FACETS on global networks from IntAct.
- Compared FACETS with gold standard datasets (MIPS, KEGG).
- Demonstrated the performance and utility of the FACETS algorithm through a case study.
Conclusions:
- FACETS provides a multi-faceted atlas of functional decompositions for PPI networks.
- The algorithm offers alternative perspectives on the functional landscape.
- FACETS aids in making sense of large volumes of interaction data.
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