A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms

Abstract. This paper proposes a novel Ant Colony Optimisation algorithm for the hierarchical problem of predicting protein functions using the Gene Ontology (GO). The GO structure represents a challenging case of hierarchical classification, since its terms are organised in a direct acyclic graph fashion where a term can have more than one parent -in contrast to only one parent in tree structures. The proposed method discovers an ordered list of classification rules which is able to predict all GO terms independently of their level. We have compared the proposed method against a baseline method, which consists of training classifiers for each GO terms individually, in five different ion-channel data sets and the results obtained are promising. Key words: hierarchical classification, ant colony optimisation, protein function prediction

• Type: Conference
• Year: 2009
• Where: EVOW
• Authors: Fernando E. B. Otero, Alex Alves Freitas, Colin G. Johnson
• Keywords: Ant Colony Optimisation, Artificial Intelligence, EVOW 2009, GO Terms, Hierarchical Classification