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

Secker, Andrew D. and Davies, Matthew N. and Freitas, Alex A. and Timmis, Jon and Clark, Edward and 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 15701166. (Full text available)

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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
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: 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 08:15
Resource URI: http://kar.kent.ac.uk/id/eprint/24125 (The current URI for this page, for reference purposes)
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