Weighted True Path Rule: a multilabel hierarchical algorithm for gene function prediction

The genome-wide hierarchical classification of gene functions, using biomolecular data from high-throughput biotechnologies, is one of the central topics in bioinformatics and functional genomics. In this paper we present a multilabel hierarchical algorithm inspired by the “true path rule” that governs both the Gene Ontology and the Functional Catalogue (FunCat). In particular we propose an enhanced version of the True Path Rule (TPR) algorithm, by which we can control the flow of information between the classifiers of the hierarchical ensemble, thus allowing to tune the precision/recall characteristics of the overall hierarchical classification system. Results with the model organism S. cerevisiae show that the proposed method significantly improves on the basic version of the TPR algorithm, as well as on the Hierarchical Top-down and Flat ensembles.