Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1755-8794
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data ; volume:11 ; number:3 ; day:14 ; month:9 ; year:2018 ; pages:19-31 ; date:9.2018
BMC medical genomics ; 11, Heft 3 (14.9.2018), 19-31, 9.2018
- Creator
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EL-Manzalawy, Yasser
- Contributor
- DOI
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10.1186/s12920-018-0388-0
- URN
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urn:nbn:de:101:1-2018102923141192522334
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:45 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- EL-Manzalawy, Yasser
- Hsieh, Tsung-Yu
- Shivakumar, Manu
- Kim, Dokyoon
- Honavar, Vasant
- SpringerLink (Online service)
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