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Updated: May 20, 2026
14:23
A Yeast 2-Hybrid Screen in Batch to Compare Protein Interactions
Published on: June 6, 2018
Neighbor overlap is enriched in the yeast interaction network: analysis and implications.
Ariel Feiglin1, John Moult, Byungkook Lee
1The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Plos One
|July 5, 2012
Summary
Neighbor Overlap, a measure of shared neighbors in protein networks, is significantly enriched in yeast. High overlap correlates with functional similarity and suggests mechanisms like protein complexes and functional redundancy.
Area of Science:
- Systems Biology
- Network Biology
- Computational Biology
Background:
- Yeast protein-protein interaction (PPI) networks exhibit complex topological features.
- These features include scale-free degree distributions and high clustering coefficients.
Purpose of the Study:
- To investigate the significance of Neighbor Overlap in the yeast PPI network.
- To explore the relationship between Neighbor Overlap and other protein attributes like sequence similarity, functional annotations, and genetic interactions.
Main Methods:
- Analysis of the yeast PPI network and comparison with carefully designed control networks.
- Quantification of Neighbor Overlap and its correlation with sequence similarity, Gene Ontology (GO) annotations, and genetic interactions.
Main Results:
- Neighbor Overlap is significantly enriched in the yeast PPI network compared to control networks.
- Proteins with high Neighbor Overlap show increased sequence similarity, GO annotation similarity, and stronger genetic interactions.
- Pairs of proteins with redundant functions exhibit high Neighbor Overlap.
Conclusions:
- Neighbor Overlap is a key feature of the yeast PPI network, exceeding expectations based on network topology alone.
- The observed enrichment suggests underlying biological principles.
- Potential mechanisms driving high Neighbor Overlap include the prevalence of protein complexes, functional redundancy (backup of function), and evolutionary adaptation for functional variation.
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