An unbalance-aware network integration method for gene function prediction

Data integration and the unbalance between functionally annotated and unannotated genes are relevant items in the context of network-based gene function prediction. Even if both these topics have been analyzed in recent works, to our knowledge no network integration methods, specific for unbalanced functional classes have been proposed in this context. We introduce an unbalance-aware network integration method based on the recently proposed COSNet algorithm, and we apply it to the genome-wide prediction of Gene Ontology terms with the M. musculus model organism.