Holden, Nicholas and Freitas, Alex A.
Hierarchical classification of G-protein-coupled receptors with a PSO/ACO algorithm.
In: IEEE Swarm Intelligence Symposium 2006, 12-14 May 2006, Indianapolis, Indiana (USA).
(Full text available)
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. This 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 between four
versions of swarm intelligence algorithms – two versions based
on our proposed algorithm and two versions based on Discrete
PSO for discovering classification rules proposed in the
literature. The experiments also compared the effectiveness of
different kinds of protein signatures when used as predictor
attributes, namely Prints, Interpro and Prosite signatures.
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