Spectral clustering gene ontology terms to group genes by function

Authors:
Nora Speer;Christian Spieth;Andreas Zell
Affiliations:
Centre for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany;Centre for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany;Centre for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany
Venue:
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Year:
2005

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Abstract

With the invention of biotechnological high throughput methods like DNA microarrays, biologists are capable of producing huge amounts of data. During the analysis of such data the need for a grouping of the genes according to their biological function arises. In this paper, we propose a method that provides such a grouping. As functional information, we use Gene Ontology terms. Our method clusters all GO terms present in a data set using a Spectral Clustering method. Then, mapping the genes back to their annotation, genes can be associated to one or more clusters of defined biological processes. We show that our Spectral Clustering method is capable of finding clusters with high inner cluster similarity.