Labeling network motifs in protein interactomes for protein function prediction

Jin Chen, Wynne Hsu, Mong Li Lee, See Kiong Ng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

51 Scopus citations

Abstract

Biological networks such as the protein-protein interaction (PPI) network have been found to contain small recurring subnetworks in significantly higher frequencies than in random networks. Such network motifs are useful for uncovering structural design principles of complex biological networks. However, current network motif finding algorithms models the PPI network as a uni-labeled graph, discovering only unlabeled and thus relatively uninformative network motifs as a result. Our objective is to exploit the currently available biological information that are associated with the vertices (the proteins) to capture not only the topological shapes of the motifs, but also the biological context in which they occurred in the PPI networks for network motif applications. We present a method called LaMoFinder to label network motifs with Gene Ontology terms in a PPI network. We also show how the resulting labeled network motifs can be used to predict unknown protein functions. Experimental results showed that the labeled network motifs extracted are biologically meaningful and can achieve better performance than existing PPI topology based methods for predicting unknown protein functions.

Original languageEnglish
Title of host publication23rd International Conference on Data Engineering, ICDE 2007
Pages546-555
Number of pages10
DOIs
StatePublished - 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: Apr 15 2007Apr 20 2007

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Conference

Conference23rd International Conference on Data Engineering, ICDE 2007
Country/TerritoryTurkey
CityIstanbul
Period4/15/074/20/07

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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