Hierarchical classification of G-protein-coupled receptors with a PSO/ACO algorithm

Holden, Nicholas and Freitas, Alex A. (2006) 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)

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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.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: data mining, bioinformatics, classification, ant colony optimization, particle swarm optimization
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:04 UTC
Last Modified: 14 Jan 2017 12:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14466 (The current URI for this page, for reference purposes)
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