AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2164
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
online resource.
- Erschienen in
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AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens ; volume:23 ; number:1 ; day:25 ; month:1 ; year:2022 ; pages:1-15 ; date:12.2022
BMC genomics ; 23, Heft 1 (25.1.2022), 1-15, 12.2022
- Urheber
-
Li, Chenkai
Sutherland, Darcy
Hammond, S. Austin
Yang, Chen
Taho, Figali
Bergman, Lauren
Houston, Simon
Warren, René L.
Wong, Titus
Hoang, Linda M. N.
Cameron, Caroline E.
Helbing, Caren C.
Birol, Inanc
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s12864-022-08310-4
- URN
-
urn:nbn:de:101:1-2022050918581102645243
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:33 MESZ
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Beteiligte
- Li, Chenkai
- Sutherland, Darcy
- Hammond, S. Austin
- Yang, Chen
- Taho, Figali
- Bergman, Lauren
- Houston, Simon
- Warren, René L.
- Wong, Titus
- Hoang, Linda M. N.
- Cameron, Caroline E.
- Helbing, Caren C.
- Birol, Inanc
- SpringerLink (Online service)
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