Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks
Author(s)
Agarwal, S
Deane, CM
Porter, MA
Jones, NS
Type
Journal Article
Abstract
The idea of “date” and “party” hubs has been influential in the study of protein–protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.
Date Issued
2010-06-17
Date Acceptance
2010-05-13
Citation
PLOS Computational Biology, 2010, 6 (6)
ISSN
1553-734X
Publisher
Public Library of Science
Journal / Book Title
PLOS Computational Biology
Volume
6
Issue
6
Copyright Statement
© 2010 Agarwal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Identifier
http://dx.doi.org/10.1371/journal.pcbi.1000817
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemical Research Methods
Mathematical & Computational Biology
Biochemistry & Molecular Biology
BIOCHEMICAL RESEARCH METHODS
MATHEMATICAL & COMPUTATIONAL BIOLOGY
BIOLOGICAL NETWORKS
FUNCTIONAL MODULES
SACCHAROMYCES-CEREVISIAE
STRUCTURAL PERSPECTIVE
SCALE DATA
COMPLEXES
DATABASE
GENOME
MAP
BETWEENNESS
Cell Physiological Phenomena
Computer Simulation
Databases, Protein
Fungal Proteins
Gene Expression Profiling
Humans
Protein Interaction Domains and Motifs
Protein Interaction Mapping
Proteins
Proteomics
Bioinformatics
06 Biological Sciences
08 Information And Computing Sciences
01 Mathematical Sciences
Publication Status
Published
Article Number
e1000817