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dc.contributor.authorArtyomov, Maxim N.
dc.contributor.authorMeissner, Alexander
dc.contributor.authorChakraborty, Arup K.
dc.date.accessioned2010-08-27T14:16:35Z
dc.date.available2010-08-27T14:16:35Z
dc.date.issued2010-05
dc.date.submitted2009-06
dc.identifier.issn1553-7358
dc.identifier.issn1553-734X
dc.identifier.urihttp://hdl.handle.net/1721.1/57580
dc.description.abstractWith relatively low efficiency, differentiated cells can be reprogrammed to a pluripotent state by ectopic expression of a few transcription factors. An understanding of the mechanisms that underlie data emerging from such experiments can help design optimal strategies for creating pluripotent cells for patient-specific regenerative medicine. We have developed a computational model for the architecture of the epigenetic and genetic regulatory networks which describes transformations resulting from expression of reprogramming factors. Importantly, our studies identify the rare temporal pathways that result in induced pluripotent cells. Further experimental tests of predictions emerging from our model should lead to fundamental advances in our understanding of how cellular identity is maintained and transformed.en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pcbi.1000785en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/en_US
dc.sourcePLoSen_US
dc.titleA model for genetic and epigenetic regulatory networks identifies rare for transcription factor induced pluripotencyen_US
dc.typeArticleen_US
dc.identifier.citationArtyomov, Maxim N., Alexander Meissner, and Arup K. Chakraborty. “A Model for Genetic and Epigenetic Regulatory Networks Identifies Rare Pathways for Transcription Factor Induced Pluripotency.” PLoS Comput Biol 6.5 (2010): e1000785.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.contributor.approverChakraborty, Arup K.
dc.contributor.mitauthorChakraborty, Arup K.
dc.contributor.mitauthorArtyomov, Maxim N.
dc.relation.journalPLoS Computational Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsArtyomov, Maxim N.; Meissner, Alexander; Chakraborty, Arup K.en
dc.identifier.orcidhttps://orcid.org/0000-0003-1268-9602
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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