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Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2006 (English)In: PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 14 / [ed] Ardil, C., World Academy of Science, Engineering and Technology , 2006, 122-127 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.

Place, publisher, year, edition, pages
World Academy of Science, Engineering and Technology , 2006. 122-127 p.
Series
Proceedings of World Academy of Science Engineering and Technology, ISSN 1307-6884 ; 14
Keyword [en]
Modules, systems biology, protein interaction networks, yeast
Identifiers
URN: urn:nbn:se:his:diva-7252ISI: 000259632400025OAI: oai:DiVA.org:his-7252DiVA: diva2:606182
Conference
Conference of the World-Academy-of-Science-Engineering-and-Technology, AUG 25-27, 2006, Prague, CZECH REPUBLIC
Available from: 2013-02-18 Created: 2013-02-18 Last updated: 2013-03-20

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http://130.203.133.150/viewdoc/summary;jsessionid=6D9F4E1FF1316988B12F47E3FE4D50BB?doi=10.1.1.193.1965

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CiteExportLink to record
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Citation style
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