Visualisation and analysis of the complexome network of Saccharomyces cerevisiae.
Li, Simone, Xu, Kai ORCID: https://orcid.org/0000-0003-2242-5440 and Wilkins, Marc R.
(2011)
Visualisation and analysis of the complexome network of Saccharomyces cerevisiae.
Journal of Proteome Research, 10
(10)
.
pp. 4744-4756.
ISSN 1535-3893
[Article]
(doi:10.1021/pr200548c)
Abstract
Most processes in the cell are delivered by protein complexes, rather than individual proteins. While the association of proteins has been studied extensively in protein–protein interaction networks (the interactome), an intuitive and effective representation of complex–complex connections (the complexome) is not yet available. Here, we describe a new representation of the complexome of Saccharomyces cerevisiae. Using the core-module-attachment data of Gavin et al. ( Nature 2006, 440, 631−6), protein complexes in the network are represented as nodes; these are connected by edges that represent shared core and/or module protein subunits. To validate this network, we examined the network topology and its distribution of biological processes. The complexome network showed scale-free characteristics, with a power law-like node degree distribution and clustering coefficient independent of node degree. Connected complexes in the network showed similarities in biological process that were nonrandom. Furthermore, clusters of interacting complexes reflected a higher-level organization of many cellular functions. The strong functional relationships seen in these clusters, along with literature evidence, allowed 44 uncharacterized complexes to be assigned putative functions using guilt-by-association. We demonstrate our network model using the GEOMI visualization platform, on which we have developed capabilities to integrate and visualize complexome data.
Item Type: | Article |
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Research Areas: | A. > School of Science and Technology > Computer Science |
Item ID: | 8412 |
Useful Links: | |
Depositing User: | Kai Xu |
Date Deposited: | 17 Feb 2012 06:45 |
Last Modified: | 30 May 2019 18:34 |
URI: | https://eprints.mdx.ac.uk/id/eprint/8412 |
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