Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/168977
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dc.contributor.authorGomez Cabrero, David-
dc.contributor.authorTarazona, Sonia-
dc.contributor.authorFerreirós Vidal, Isabel-
dc.contributor.authorRamirez, Ricardo N.-
dc.contributor.authorCompany, Carlos-
dc.contributor.authorSchmidt, Andreas-
dc.contributor.authorReijmers, Theo-
dc.contributor.authorvon Saint Paul, Veronica-
dc.contributor.authorMarabita, Francesco-
dc.contributor.authorRodríguez Ubreva, Javier-
dc.contributor.authorGarcía Gómez, Antonio-
dc.contributor.authorCarroll, Tom-
dc.contributor.authorCooper, Lee-
dc.contributor.authorLiang, Ziwei-
dc.contributor.authorDharmalingam, Gopuraja-
dc.contributor.authorvan der Kloet, Frans-
dc.contributor.authorHarms, Amy C.-
dc.contributor.authorBalzano Nogueira, Leandro-
dc.contributor.authorLagani, Vincenzo-
dc.contributor.authorTsamardinos, Ioannis-
dc.contributor.authorLappe, Michael-
dc.contributor.authorMaier, Dieter-
dc.contributor.authorWesterhuis, Johan A.-
dc.contributor.authorHankemeier, Thomas-
dc.contributor.authorImhof, Axel-
dc.contributor.authorBallestar Tarín, Esteban-
dc.contributor.authorMortazavi, Ali-
dc.contributor.authorMerkenschlager, Matthias-
dc.contributor.authorEgner, Jesper-
dc.contributor.authorConesa, Ana-
dc.date.accessioned2020-07-17T08:55:56Z-
dc.date.available2020-07-17T08:55:56Z-
dc.date.issued2019-10-31-
dc.identifier.urihttp://hdl.handle.net/2445/168977-
dc.description.abstractMulti-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STAT egra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes-
dc.format.extent15 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherNature Publishing Group-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1038/s41597-019-0202-7-
dc.relation.ispartofScientific Data, 2019, vol. 6, p. 256-
dc.relation.urihttps://doi.org/10.1038/s41597-019-0202-7-
dc.rightscc by (c) Gomez Cabrero et al., 2019-
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/-
dc.sourceArticles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))-
dc.subject.classificationFisiologia cel·lular-
dc.subject.classificationCèl·lules B-
dc.subject.classificationRatolins (Animals de laboratori)-
dc.subject.otherCell physiology-
dc.subject.otherB cells-
dc.subject.otherMice (Laboratory animals)-
dc.titleSTATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.date.updated2020-07-17T08:03:26Z-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/306000/EU//STATEGRA-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid31672995-
Appears in Collections:Publicacions de projectes de recerca finançats per la UE
Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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