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Authors: Fernando Benites and Elena Sapozhnikova

Affiliation: University of Konstanz, Germany

ISBN: 978-989-8565-35-8

Keyword(s): Data Mining, Bioinformatics, Generalized Association Rules, Gene Ontology.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Data Mining and Machine Learning ; Databases and Data Management ; Genomics and Proteomics

Abstract: The constantly increasing volume and complexity of available biological data requires new methods for managing and analyzing them. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining generalized association rules connecting their categories. To select only the most important rules, we propose a new interestingness measure especially well-suited for hierarchically organized rules. To demonstrate this approach, we applied it to the bioinformatics domain and, more specifically, to the analysis of data from Gene Ontology, Cell type Ontology and GPCR databases. In this way found association rules connecting two biological ontologies can provide the user with new knowledge about underlying biological processes. The preliminary results show that produced rules represent meaningful and quite relia ble associations among the ontologies and help infer new knowledge. (More)

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Paper citation in several formats:
Benites, F. and Sapozhnikova, E. (2013). Generalized Association Rules for Connecting Biological Ontologies.In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013) ISBN 978-989-8565-35-8, pages 229-236. DOI: 10.5220/0004327102290236

@conference{bioinformatics13,
author={Fernando Benites. and Elena Sapozhnikova.},
title={Generalized Association Rules for Connecting Biological Ontologies},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)},
year={2013},
pages={229-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004327102290236},
isbn={978-989-8565-35-8},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)
TI - Generalized Association Rules for Connecting Biological Ontologies
SN - 978-989-8565-35-8
AU - Benites, F.
AU - Sapozhnikova, E.
PY - 2013
SP - 229
EP - 236
DO - 10.5220/0004327102290236

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