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Authors: Hasan Oğul and Onur Altındağ

Affiliation: Baskent University, Turkey

ISBN: 978-989-8565-41-9

Keyword(s): Tumor Classification, Gene Expression, Data Integration, Feature Selection, MicroRNA Regulation.

Related Ontology Subjects/Areas/Topics: Applications ; Bioinformatics and Systems Biology ; Pattern Recognition ; Software Engineering

Abstract: Classifying cancer samples from gene expression data is one of the central problems in current systems biomedicine. The problem is challenging due to the small number of samples in comparison to the number of genes (mRNAs) in a typical microarray experiment. Recent reports suggest that feature selection may help to manage the problem. Furthermore, microRNA expression profiles have shown to provide valuable knowledge in detecting cancer signatures. In this study, we present the results of a comprehensive study to assess the effect of feature selection and microRNA-mRNA data integration in cancer type prediction from microarray expression data. We prove that this integration can significantly improve prediction accuracy with a proper feature selection strategy.

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Paper citation in several formats:
Oğul, H. and Altındağ, O. (2013). Integrating MicroRNA and mRNA Expression Data for Cancer Classification.In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 503-507. DOI: 10.5220/0004334405030507

@conference{icpram13,
author={Hasan Oğul. and Onur Altındağ.},
title={Integrating MicroRNA and mRNA Expression Data for Cancer Classification},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={503-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004334405030507},
isbn={978-989-8565-41-9},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Integrating MicroRNA and mRNA Expression Data for Cancer Classification
SN - 978-989-8565-41-9
AU - Oğul, H.
AU - Altındağ, O.
PY - 2013
SP - 503
EP - 507
DO - 10.5220/0004334405030507

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