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dc.contributor.authorClarke, David C.
dc.contributor.authorLauffenburger, Douglas A.
dc.date.accessioned2014-12-12T19:10:16Z
dc.date.available2014-12-12T19:10:16Z
dc.date.issued2012-02
dc.date.submitted2011-07
dc.identifier.issn0300-5127
dc.identifier.issn1470-8752
dc.identifier.urihttp://hdl.handle.net/1721.1/92297
dc.description.abstractInflammation is a key physiological response to infection and injury and, although usually beneficial, it can also be damaging to the host. The liver is a prototypical example in this regard because inflammation helps to resolve liver injury, but it also underlies the aetiology of pathologies such as fibrosis and hepatocellular carcinoma. Liver cells sense their environment, including the inflammatory environment, through the activities of receptor-mediated signal transduction pathways. These pathways are organized in a complex interconnected network, and it is becoming increasingly recognized that cellular adaptations result from the quantitative integration of multi-pathway network activities, rather than isolated pathways causing particular phenotypes. Therefore comprehending liver cell signalling in inflammation requires a scientific approach that is appropriate for studying complex networks. In the present paper, we review our application of systems analyses of liver cell signalling in response to inflammatory environments. Our studies feature broad measurements of cell signalling and phenotypes in response to numerous experimental perturbations reflective of inflammatory environments, the data from which are analysed using Boolean and fuzzy logic models and regression-based methods in order to quantitatively relate the phenotypic responses to cell signalling network states. Our principal biological insight from these studies is that hepatocellular carcinoma cells feature uncoupled inflammatory and growth factor signalling, which may underlie their immune evasion and hyperproliferative properties.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (grant number R24-DK090963)en_US
dc.description.sponsorshipMIT Center for Cellular Decision Processes (grant number NIH P50-GM68762)en_US
dc.description.sponsorshipUnited States. Army Research Office (Institute for Collaborative Biotechnologies (contract number W911NF-09-D-0001))en_US
dc.language.isoen_US
dc.publisherPortland Press on behalf of the Biochemical Societyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1042/bst20110633en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Lauffenburger via Howard Silveren_US
dc.titleMulti-pathway network analysis of mammalian epithelial cell responses in inflammatory environmentsen_US
dc.typeArticleen_US
dc.identifier.citationClarke, David C., and Douglas A. Lauffenburger. “Multi-Pathway Network Analysis of Mammalian Epithelial Cell Responses in Inflammatory Environments.” Biochem. Soc. Trans. 40, no. 1 (January 19, 2012): 133–138.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Cell Decision Process Centeren_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.approverLauffenburger, Douglas A.en_US
dc.contributor.mitauthorClarke, David C.en_US
dc.contributor.mitauthorLauffenburger, Douglas A.en_US
dc.relation.journalBiochemical Society Transactionsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsClarke, David C.; Lauffenburger, Douglas A.en_US
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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