Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1476-4598
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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online resource.
- Erschienen in
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Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality ; volume:20 ; number:1 ; day:28 ; month:8 ; year:2021 ; pages:1-22 ; date:12.2021
Molecular cancer ; 20, Heft 1 (28.8.2021), 1-22, 12.2021
- Urheber
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1186/s12943-021-01405-8
- URN
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urn:nbn:de:101:1-2021111305365186188422
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:21 MESZ
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Beteiligte
- Benfatto, Salvatore
- Serçin, Özdemirhan
- Dejure, Francesca Romana
- Abdollahi, Amir
- Zenke, Frank T.
- Mardin, Balca
- SpringerLink (Online service)
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