Predicting functional effects of ion channel variants using new phenotypic machine learning methods

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dc.contributor.author Hedrich, Ulrike B. S.
dc.contributor.author Lerche, Holger
dc.contributor.author Pfeifer, Nico
dc.contributor.author Boßelmann, Christian Malte
dc.date.accessioned 2023-08-21T05:01:52Z
dc.date.available 2023-08-21T05:01:52Z
dc.date.issued 2023
dc.identifier.issn 1553-734X
dc.identifier.uri http://hdl.handle.net/10900/144426
dc.language.iso en de_DE
dc.publisher Public Library Science de_DE
dc.relation.uri http://dx.doi.org/10.1371/journal.pcbi.1010959 de_DE
dc.subject.ddc 570 de_DE
dc.subject.ddc 600 de_DE
dc.title Predicting functional effects of ion channel variants using new phenotypic machine learning methods de_DE
dc.type Article de_DE
utue.quellen.id 20230619000000_00910
utue.personen.roh Bosselmann, Christian Malte
utue.personen.roh Hedrich, Ulrike B. S.
utue.personen.roh Lerche, Holger
utue.personen.roh Pfeifer, Nico
dcterms.isPartOf.ZSTitelID Plos Computational Biology de_DE
dcterms.isPartOf.ZS-Issue Article e1010959 de_DE
dcterms.isPartOf.ZS-Volume 19 (3) de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE
utue.fakultaet 07 Mathematisch-Naturwissenschaftliche Fakultät de_DE


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