Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2399-3669
- 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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Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds ; volume:5 ; number:1 ; day:18 ; month:10 ; year:2022 ; pages:1-11 ; date:12.2022
Communications chemistry ; 5, Heft 1 (18.10.2022), 1-11, 12.2022
- Urheber
-
Korshunova, Maria
Huang, Niles
Capuzzi, Stephen
Radchenko, Dmytro
Savych, Olena
Moroz, Yuriy S.
Wells, Carrow I.
Willson, Timothy M.
Tropsha, Alexander
Isayev, Olexandr
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1038/s42004-022-00733-0
- URN
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urn:nbn:de:101:1-2023010321153722840808
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:26 MESZ
Datenpartner
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Beteiligte
- Korshunova, Maria
- Huang, Niles
- Capuzzi, Stephen
- Radchenko, Dmytro
- Savych, Olena
- Moroz, Yuriy S.
- Wells, Carrow I.
- Willson, Timothy M.
- Tropsha, Alexander
- Isayev, Olexandr
- SpringerLink (Online service)
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