A hierarchical multi-label classification ant colony algorithm for protein function prediction

Otero, Fernando E.B. and Freitas, Alex A. and Johnson, Colin G. (2010) A hierarchical multi-label classification ant colony algorithm for protein function prediction. Memetic Computing, 2 (3). pp. 165-181. ISSN 1865-9284. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1007/s12293-010-0045-4

Abstract

This paper proposes a novel ant colony optimisation (ACO) algorithm tailored for the hierarchical multi-label classification problem of protein function prediction. This problem is a very active research field, given the large increase in the number of uncharacterised proteins available for analysis and the importance of determining their functions in order to improve the current biological knowledge. Since it is known that a protein can perform more than one function and many protein functional-definition schemes are organised in a hierarchical structure, the classification problem in this case is an instance of a hierarchical multi-label problem. In this type of problem, each example may belong to multiple class labels and class labels are organised in a hierarchical structure—either a tree or a directed acyclic graph structure. It presents a more complex problem than conventional flat classification, given that the classification algorithm has to take into account hierarchical relationships between class labels and be able to predict multiple class labels for the same example. The proposed ACO algorithm discovers an ordered list of hierarchical multi-label classification rules. It is evaluated on sixteen challenging bioinformatics data sets involving hundreds or thousands of class labels to be predicted and compared against state-of-the-art decision tree induction algorithms for hierarchical multi-label classification.

Item Type: Article
Uncontrolled keywords: determinacy analysis, Craig interpolants
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Depositing User: Colin Johnson
Date Deposited: 21 Sep 2012 09:49
Last Modified: 19 May 2014 15:53
Resource URI: http://kar.kent.ac.uk/id/eprint/30634 (The current URI for this page, for reference purposes)
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