HIERARCHICAL CLASSIFICATION OF G-PROTEIN-COUPLED RECEPTORS WITH A PSO/ACO ALGORITHM

In our previous work we have proposed a hybrid Particle Swarm Optimisation / Ant Colony Optimisation (PSO/ACO) algorithm for discovering classification rules. In this paper we propose some modifications to the algorithm and apply it to a challenging hierarchical classification problem. Th is is a bioinformatics problem involving the prediction of G-Protein- Coupled Receptor's (GPCR) hierarchical functional classes. We report the results of an extensive comparison betwe en four versions of swarm intelligence algorithms - two ver sions based on our proposed algorithm and two versions based on Discrete PSO for discovering classification rules proposed i n the literature. The experiments also compared the effec tiveness of different kinds of protein signatures when used as predictor attributes, namely Prints, Interpro and Prosite sig natures.