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• W2168118433 abstract "Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein-protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc." @default.
• W2168118433 created "2016-06-24" @default.
• W2168118433 creator A5023619547 @default.
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• W2168118433 date "2012-05-25" @default.
• W2168118433 modified "2023-09-26" @default.
• W2168118433 title "CombFunc: predicting protein function using heterogeneous data sources" @default.
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• W2168118433 doi "https://doi.org/10.1093/nar/gks489" @default.
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