Fuzzy Subgroup Mining for Gene Associations
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
When studying the therapeutic efficacy of potential new drugs, it would be much more efficient to use predictors in order to assess their toxicity before going into clinical trials. One promising line of research has focused on the discovery of sets of candidate gene profiles to be used as toxicity indicators in future drug development. In particular genomic microarrays may be used to analyze the causality relationship between the administration of the drugs and the so-called gene expression, a parameter typically used by biologists to measure its influence at gene level. This kind of experiments involves a high throughput analysis of noisy and particularly unreliable data, which makes the application of many data mining techniques very difficult. In this paper we explore a fuzzy formulation of the a priori algorithm, a technique whose crisp version is commonly used to mine for subgroups in large datasets; the purpose is to extend the original method, already suitable to deal with large amount of data, in a way that naturally allows the user to deal with the intrinsic imprecision in the data. The algorithm is tested on real data coming from experimental genomic data.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
ORTOLANI, Marco, Ondine CALLAN, Michael R. BERTHOLD, David E. PATTERSON, 2004. Fuzzy Subgroup Mining for Gene Associations. IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.. Banff, Alta., Canada, 27. Juni 2004 - 30. Juni 2004. In: IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.. IEEE, 2004, pp. 560-565 Vol.2. ISBN 0-7803-8376-1. Available under: doi: 10.1109/NAFIPS.2004.1337362BibTex
@inproceedings{Ortolani2004Fuzzy-24405, year={2004}, doi={10.1109/NAFIPS.2004.1337362}, title={Fuzzy Subgroup Mining for Gene Associations}, isbn={0-7803-8376-1}, publisher={IEEE}, booktitle={IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.}, pages={560--565 Vol.2}, author={Ortolani, Marco and Callan, Ondine and Berthold, Michael R. and Patterson, David E.} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/24405"> <dc:contributor>Berthold, Michael R.</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24405/2/Ortolani_244050.pdf"/> <dc:creator>Ortolani, Marco</dc:creator> <dc:language>eng</dc:language> <dc:contributor>Callan, Ondine</dc:contributor> <dcterms:abstract xml:lang="eng">When studying the therapeutic efficacy of potential new drugs, it would be much more efficient to use predictors in order to assess their toxicity before going into clinical trials. One promising line of research has focused on the discovery of sets of candidate gene profiles to be used as toxicity indicators in future drug development. In particular genomic microarrays may be used to analyze the causality relationship between the administration of the drugs and the so-called gene expression, a parameter typically used by biologists to measure its influence at gene level. This kind of experiments involves a high throughput analysis of noisy and particularly unreliable data, which makes the application of many data mining techniques very difficult. In this paper we explore a fuzzy formulation of the a priori algorithm, a technique whose crisp version is commonly used to mine for subgroups in large datasets; the purpose is to extend the original method, already suitable to deal with large amount of data, in a way that naturally allows the user to deal with the intrinsic imprecision in the data. The algorithm is tested on real data coming from experimental genomic data.</dcterms:abstract> <dc:contributor>Patterson, David E.</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dcterms:issued>2004</dcterms:issued> <dc:contributor>Ortolani, Marco</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-09-12T13:14:45Z</dc:date> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-09-12T13:14:45Z</dcterms:available> <dc:creator>Berthold, Michael R.</dc:creator> <dc:creator>Patterson, David E.</dc:creator> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24405/2/Ortolani_244050.pdf"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24405"/> <dc:creator>Callan, Ondine</dc:creator> <dc:rights>terms-of-use</dc:rights> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:title>Fuzzy Subgroup Mining for Gene Associations</dcterms:title> <dcterms:bibliographicCitation>NAFIPS 2004 : 2004 Annual Meeting of the North American Fuzzy Information Processing Society ; fuzzy sets in the heart of the Canadian Rockies, Banff, Alberta, Canada, June 27 - 30, 2004 / Scott Dick (ed.). - Piscataway, NJ : IEEE Operations Center, 2004. - S. 560-565. - ISBN 0-7803-8376-1</dcterms:bibliographicCitation> <foaf:homepage rdf:resource="http://localhost:8080/"/> </rdf:Description> </rdf:RDF>