A hierarchical classification ant colony algorithm for predicting gene ontology terms

Otero, Fernando E.B. and Freitas, Alex A. and Johnson, Colin G. (2009) A hierarchical classification ant colony algorithm for predicting gene ontology terms. In: Proc. 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBio-2009), APR 15-17, 2009, Tubingen, GERMANY. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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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.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: ant colony optimization, data mining, classification, bioinformatics
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:16
Last Modified: 20 May 2014 09:08
Resource URI: https://kar.kent.ac.uk/id/eprint/24128 (The current URI for this page, for reference purposes)
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