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Authors: Son T. Nguyen and Colin G. Johnson

Affiliation: University of Kent, United Kingdom

Keyword(s): Protein Secondary Structure Prediction, Classification Bayesian Neural Network, Optimised Network Architecture.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Enterprise Information Systems ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Based Data Mining and Complex Information Processing ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: The prediction of protein secondary structure is a topic that has been tackled by many researchers in the field of bioinformatics. In previous work, this problem has been solved by various methods including the use of traditional classification neural networks with the standard error back-propagation training algorithm. Since the traditional neural network may have a poor generalisation, the Bayesian technique has been used to improve the generalisation and the robustness of these networks. This paper describes the use of optimised classification Bayesian neural networks for the prediction of protein secondary structure. The well-known RS126 dataset was used for network training and testing. The experimental results show that the optimised classification Bayesian neural network can reach an accuracy greater than 75%.

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Paper citation in several formats:
T. Nguyen, S. and G. Johnson, C. (2013). Protein Secondary Structure Prediction using an Optimised Bayesian Classification Neural Network. In Proceedings of the 5th International Joint Conference on Computational Intelligence - NCTA, (IJCCI 2013) ISBN 978-989-8565-77-8; ISSN 2184-2825, pages 451-457. DOI: 10.5220/0004538604510457

@conference{ncta13,
author={Son {T. Nguyen}. and Colin {G. Johnson}.},
title={Protein Secondary Structure Prediction using an Optimised Bayesian Classification Neural Network},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - NCTA, (IJCCI 2013)},
year={2013},
pages={451-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004538604510457},
isbn={978-989-8565-77-8},
issn={2184-2825},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - NCTA, (IJCCI 2013)
TI - Protein Secondary Structure Prediction using an Optimised Bayesian Classification Neural Network
SN - 978-989-8565-77-8
IS - 2184-2825
AU - T. Nguyen, S.
AU - G. Johnson, C.
PY - 2013
SP - 451
EP - 457
DO - 10.5220/0004538604510457