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Authors: Saras Saraswathi ; Robert L. Jernigan and Andrzej Kloczkowski

Affiliation: L. H. Baker Center for Bioinformatics and Biological Statistics and Iowa State University, United States

ISBN: 978-989-8425-32-4

Keyword(s): Relative solvent accessibility, Support vector machine, Neural network, Extreme learning machine, Prediction.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Higher Level Artificial Neural Network Based Intelligent Systems ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neuroinformatics and Bioinformatics ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Supervised and Unsupervised Learning ; Support Vector Machines and Applications ; Theory and Methods

Abstract: A neural network based method called Sparse-Extreme Learning Machine (S-ELM) is used for prediction of Relative Solvent Accessibility (RSA) in proteins. We have shown that multiple-fold gains in speed of processing by S-ELM compared to using SVM for classification, while accuracy efficiencies are comparable to literature. The study indicates that using S-ELM would give a distinct advantage in terms of processing speed and performance for RSA prediction.

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Paper citation in several formats:
Saraswathi, S.; Jernigan, R. and Kloczkowski, A. (2010). AN EXTREME LEARNING MACHINE CLASSIFIER FOR PREDICTION OF RELATIVE SOLVENT ACCESSIBILITY IN PROTEINS .In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 364-369. DOI: 10.5220/0003086803640369

@conference{icnc10,
author={Saras Saraswathi. and Robert L. Jernigan. and Andrzej Kloczkowski.},
title={AN EXTREME LEARNING MACHINE CLASSIFIER FOR PREDICTION OF RELATIVE SOLVENT ACCESSIBILITY IN PROTEINS },
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={364-369},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003086803640369},
isbn={978-989-8425-32-4},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - AN EXTREME LEARNING MACHINE CLASSIFIER FOR PREDICTION OF RELATIVE SOLVENT ACCESSIBILITY IN PROTEINS
SN - 978-989-8425-32-4
AU - Saraswathi, S.
AU - Jernigan, R.
AU - Kloczkowski, A.
PY - 2010
SP - 364
EP - 369
DO - 10.5220/0003086803640369

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