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Prediction of Gene Ontology Annotations Based on Gene Functional Clustering

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3 Author(s)
Marco Tagliasacchi ; Dipt. di Elettron. e Inf., Politec. di Milano, Milan, Italy ; Roberto Sarati ; Marco Masseroli

We propose an algorithm that predicts potentially missing Gene Ontology annotations, in order to speed up the time-consuming annotation curation process. The proposed method extends a previous work based on the singular value decomposition of the gene-term annotation matrix and incorporates gene clustering, based on gene functional similarity computed by means of the Gene Ontology annotations. We tested the prediction method by performing K-fold cross-validation on the genomes of two organisms, Saccharomyces cerevisiae (SGD) and Drosophila melanogaster (FlyBase).

Published in:

BioInformatics and BioEngineering (BIBE), 2010 IEEE International Conference on

Date of Conference:

May 31 2010-June 3 2010