SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2045-2322
- 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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SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites ; volume:8 ; number:1 ; day:26 ; month:7 ; year:2018 ; pages:1-9 ; date:12.2018
Scientific reports ; 8, Heft 1 (26.7.2018), 1-9, 12.2018
- Klassifikation
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Biowissenschaften, Biologie
- Urheber
-
AL-barakati, Hussam J.
- Beteiligte Personen und Organisationen
-
McConnell, Evan W.
Hicks, Leslie M.
Poole, Leslie B.
Newman, Robert H.
KC, Dukka B.
SpringerLink (Online service)
- DOI
-
10.1038/s41598-018-29126-x
- URN
-
urn:nbn:de:101:1-2018092322315290124531
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:27 MESZ
Datenpartner
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Beteiligte
- AL-barakati, Hussam J.
- McConnell, Evan W.
- Hicks, Leslie M.
- Poole, Leslie B.
- Newman, Robert H.
- KC, Dukka B.
- SpringerLink (Online service)
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