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Comparing signaling networks between normal and transformed hepatocytes using discrete logical models

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dc.contributor.author Saez-Rodriguez, J en
dc.contributor.author Alexopoulos, LG en
dc.contributor.author Zhang, MS en
dc.contributor.author Morris, MK en
dc.contributor.author Lauffenburger, DA en
dc.contributor.author Sorger, PK en
dc.date.accessioned 2014-03-01T02:01:53Z
dc.date.available 2014-03-01T02:01:53Z
dc.date.issued 2011 en
dc.identifier.issn 00085472 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/29262
dc.subject.other 4 (2 aminoethylamino) 1,8 dimethylimidazo[1,2 a]quinoxaline en
dc.subject.other epidermal growth factor en
dc.subject.other epidermal growth factor receptor en
dc.subject.other glycogen synthase kinase 3 en
dc.subject.other heat shock protein 27 en
dc.subject.other I kappa B kinase inhibitor en
dc.subject.other immunoglobulin enhancer binding protein en
dc.subject.other insulin en
dc.subject.other insulin receptor substrate en
dc.subject.other interleukin 1alpha en
dc.subject.other interleukin 6 en
dc.subject.other Janus kinase en
dc.subject.other mammalian target of rapamycin en
dc.subject.other mitogen activated protein kinase en
dc.subject.other phosphatidylinositol 3 kinase inhibitor en
dc.subject.other protein kinase B en
dc.subject.other protein p85 en
dc.subject.other Ras protein en
dc.subject.other STAT protein en
dc.subject.other transforming growth factor alpha en
dc.subject.other tumor necrosis factor alpha en
dc.subject.other article en
dc.subject.other cancer cell culture en
dc.subject.other cell transformation en
dc.subject.other controlled study en
dc.subject.other down regulation en
dc.subject.other enzyme activation en
dc.subject.other enzyme activity en
dc.subject.other human en
dc.subject.other human cell en
dc.subject.other information science en
dc.subject.other liver cell en
dc.subject.other mathematical model en
dc.subject.other prior knowledge network en
dc.subject.other priority journal en
dc.subject.other protein degradation en
dc.subject.other protein localization en
dc.subject.other protein phosphorylation en
dc.subject.other protein protein interaction en
dc.subject.other signal transduction en
dc.subject.other statistical analysis en
dc.subject.other upregulation en
dc.subject.other Cell Line, Transformed en
dc.subject.other Cell Line, Tumor en
dc.subject.other Hepatocytes en
dc.subject.other Humans en
dc.subject.other Models, Biological en
dc.subject.other Signal Transduction en
dc.title Comparing signaling networks between normal and transformed hepatocytes using discrete logical models en
heal.type journalArticle en
heal.identifier.primary 10.1158/0008-5472.CAN-10-4453 en
heal.identifier.secondary http://dx.doi.org/10.1158/0008-5472.CAN-10-4453 en
heal.publicationDate 2011 en
heal.abstract Substantial effort in recent years has been devoted to constructing and analyzing large-scale gene and protein networks on the basis of ""omic"" data and literature mining. These interaction graphs provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or drugs. Conversely, traditional approaches to analyzing cell signaling are narrow in scope and cannot easily make use of network-level data. Here, we combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data. Specifically, we created Boolean logic models of immediate-early signaling in liver cells by training a literature-based prior knowledge network against biochemical data obtained from primary human hepatocytes and 4 hepatocellular carcinoma cell lines exposed to combinations of cytokines and small-molecule kinase inhibitors. Distinct families of models were recovered for each cell type, and these families clustered topologically into normal and diseased sets. ©2011 AACR. en
heal.journalName Cancer Research en
dc.identifier.doi 10.1158/0008-5472.CAN-10-4453 en
dc.identifier.volume 71 en
dc.identifier.issue 16 en
dc.identifier.spage 5400 en
dc.identifier.epage 5411 en


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