DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome

dc.contributor.author	Zeng, Wenhuan
dc.contributor.author	Gautam, Anupam
dc.contributor.author	Huson, Daniel
dc.date.accessioned	2023-04-19T13:30:35Z
dc.date.available	2023-04-19T13:30:35Z
dc.date.issued	2022
dc.identifier.issn	1367-4803
dc.identifier.uri	http://hdl.handle.net/10900/139329
dc.language.iso	en	en
dc.publisher	Oxford Univ Press	de_DE
dc.relation.uri	http://dx.doi.org/10.1093/bioinformatics/btac584
dc.subject.ddc	570	de_DE
dc.subject.ddc	004	de_DE
dc.subject.ddc	600	de_DE
dc.subject.ddc	510	de_DE
dc.title	DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome	de_DE
dc.type	Article	de_DE
utue.quellen.id	20230202000000_01714
utue.publikation.seiten	4670-4676	de_DE
utue.personen.roh	Zeng, Wenhuan
utue.personen.roh	Gautam, Anupam
utue.personen.roh	Huson, Daniel H.
dcterms.isPartOf.ZSTitelID	Bioinformatics	de_DE
dcterms.isPartOf.ZS-Issue	20	de_DE
dcterms.isPartOf.ZS-Volume	38	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät
utue.fakultaet	Sonstige