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dc.contributor.authorKrismer, Konstantin
dc.contributor.authorBird, Molly A
dc.contributor.authorVarmeh, Shohreh
dc.contributor.authorHandly, Erika D
dc.contributor.authorGattinger, Anna
dc.contributor.authorBernwinkler, Thomas
dc.contributor.authorAnderson, Daniel A
dc.contributor.authorHeinzel, Andreas
dc.contributor.authorJoughin, Brian A
dc.contributor.authorKong, Yi Wen
dc.contributor.authorCannell, Ian G
dc.contributor.authorYaffe, Michael B
dc.date.accessioned2021-10-27T19:58:16Z
dc.date.available2021-10-27T19:58:16Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/134134
dc.description.abstract© 2020 The Author(s) Krismer et al. present a computational approach to identify RNA-binding proteins (RBPs) that modulate post-transcriptional control of gene expression using RNA expression data as inputs. By applying this approach to publicly available patient datasets, they identify and experimentally confirm that the RBP hnRNPC contributes to chemotherapy resistance in lung cancer.
dc.language.isoen
dc.publisherElsevier BV
dc.relation.isversionof10.1016/j.celrep.2020.108064
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs License
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScientific Reports
dc.titleTransite: A Computational Motif-Based Analysis Platform That Identifies RNA-Binding Proteins Modulating Changes in Gene Expression
dc.typeArticle
dc.relation.journalCell Reports
dc.eprint.versionFinal published version
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2021-08-04T15:09:52Z
dspace.orderedauthorsKrismer, K; Bird, MA; Varmeh, S; Handly, ED; Gattinger, A; Bernwinkler, T; Anderson, DA; Heinzel, A; Joughin, BA; Kong, YW; Cannell, IG; Yaffe, MB
dspace.date.submission2021-08-04T15:09:58Z
mit.journal.volume32
mit.journal.issue8
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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