Inferring secretory and metabolic pathway activity from omic data with secCellFie

dc.contributor.author	Weiß, Linus
dc.date.accessioned	2025-07-22T05:30:22Z
dc.date.available	2025-07-22T05:30:22Z
dc.date.issued	2024
dc.identifier.issn	1096-7176
dc.identifier.uri	http://hdl.handle.net/10900/168272
dc.language.iso	en	de_DE
dc.publisher	San Diego : Academic Press Inc Elsevier Science	de_DE
dc.relation.uri	http://dx.doi.org/10.1016/j.ymben.2023.12.006	de_DE
dc.subject.ddc	570	de_DE
dc.title	Inferring secretory and metabolic pathway activity from omic data with secCellFie	de_DE
dc.type	Article	de_DE
utue.quellen.id	20240422000000_01001
utue.publikation.seiten	273-285	de_DE
utue.personen.roh	Samoudi, Mojtaba
utue.personen.roh	Robinson, Caressa M.
utue.personen.roh	Kuo, Chih-Chung
utue.personen.roh	Weiss, Linus
utue.personen.roh	Doha, Km Shams Ud
utue.personen.roh	Campos, Alex
utue.personen.roh	Tejwani, Vijay
utue.personen.roh	Dahodwala, Hussain
utue.personen.roh	Menard, Patrice
utue.personen.roh	Voldborg, Bjorn G.
utue.personen.roh	Robasky, Bradley
utue.personen.roh	Sharfstein, Susan T.
utue.personen.roh	Lewis, Nathan E.
dcterms.isPartOf.ZSTitelID	Metabolic Engineering	de_DE
dcterms.isPartOf.ZS-Volume	81	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE