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An artificial immune system for clustering amino acids in the context of protein function classification

Secker, Andrew D., Davies, Matthew N., Freitas, Alex A., Timmis, Jon, Clark, Edward, Flower, Darren R. (2009) An artificial immune system for clustering amino acids in the context of protein function classification. Journal of Mathematical Modelling and Algorithms, 8 . pp. 103-123. ISSN 1570-1166. (doi:10.1007/s10852-009-9107-3) (KAR id:24125)

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Official URL
http://dx.doi.org/10.1007/s10852-009-9107-3

Abstract

This paper addresses the classification task of data mining (a form of supervised learning) in the context of an important bioinformatics problem, namely the prediction of protein functions. This problem is cast as a hierarchical classification problem. The protein functions to be predicted correspond to classes that are arranged in a hierarchical structure (this takes the form of a class tree). The main contribution of this paper is to propose a new Artificial Immune System that creates a new representation for proteins, in order to maximize the predictive accuracy of a hierarchical classification algorithm applied to the corresponding protein function prediction problem.

Item Type: Article
DOI/Identification number: 10.1007/s10852-009-9107-3
Uncontrolled keywords: data mining, artificial immune systems, clustering, protein function prediction
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:16 UTC
Last Modified: 16 Feb 2021 12:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/24125 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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