An Artificial Immune System for Evolving Amino Acid Clusters Tailored to Protein Function Prediction

Authors:
A. Secker;M. N. Davies;A. A. Freitas;J. Timmis;E. Clark;D. R. Flower
Affiliations:
Computing Laboratory and Centre for BioMedical Informatics, University of Kent, Canterbury, UK CT2 7NF;The Jenner Institute, University of Oxford, Compton, Newbury, UK RG20 7NN;Computing Laboratory and Centre for BioMedical Informatics, University of Kent, Canterbury, UK CT2 7NF;Departments of Computer Science and Electronics, University of York, York, UK YO10 5DD;Departments of Computer Science and Electronics, University of York, York, UK YO10 5DD;The Jenner Institute, University of Oxford, Compton, Newbury, UK RG20 7NN
Venue:
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Year:
2008

Citing 4
Cited 1

Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
On the hierarchical classification of G protein-coupled receptors

Bioinformatics
On diversity and artificial immune systems: incorporating a diversity operator into ainet

WIRN'05 Proceedings of the 16th Italian conference on Neural Nets

Review Article: Recent Advances in Artificial Immune Systems: Models and Applications

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

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.