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An artificial immune system for evolving amino acid clusters tailored to protein function prediction

Authors :
Bentley, Peter J.
Lee, Doheon
Jung, Sungwon
Secker, Andrew D.
Davies, Matthew N.
Freitas, Alex A.
Timmis, Jon
Clark, Edward
Flower, Darren R.
Bentley, Peter J.
Lee, Doheon
Jung, Sungwon
Secker, Andrew D.
Davies, Matthew N.
Freitas, Alex A.
Timmis, Jon
Clark, Edward
Flower, Darren R.
Publication Year :
2008

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, where the protein functions to be predicted correspond to classes that are arranged in a hierarchical structure, in 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.

Details

Database :
OAIster
Notes :
An artificial immune system for evolving amino acid clusters tailored to protein function prediction
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn899125769
Document Type :
Electronic Resource