The logic of EGFR/ErbB signaling: Theoretical properties and analysis of high-throughput data

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dc.contributor.author Samaga, R en
dc.contributor.author Saez-Rodriguez, J en
dc.contributor.author Alexopoulos, LG en
dc.contributor.author Sorger, PK en
dc.contributor.author Klamt, S en
dc.date.accessioned 2014-03-01T01:32:10Z
dc.date.available 2014-03-01T01:32:10Z
dc.date.issued 2009 en
dc.identifier.issn 1553-734X en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/20056
dc.subject High Throughput en
dc.subject.classification Biochemical Research Methods en
dc.subject.classification Mathematical & Computational Biology en
dc.subject.other epidermal growth factor receptor en
dc.subject.other mitogen activated protein kinase en
dc.subject.other mitogen activated protein kinase p38 en
dc.subject.other stress activated protein kinase en
dc.subject.other analysis en
dc.subject.other article en
dc.subject.other cell line en
dc.subject.other data analysis en
dc.subject.other high throughput screening en
dc.subject.other information science en
dc.subject.other liver cell en
dc.subject.other logic en
dc.subject.other mammal cell en
dc.subject.other mathematical model en
dc.subject.other predictive validity en
dc.subject.other proteomics en
dc.subject.other qualitative analysis en
dc.subject.other signal transduction en
dc.subject.other stimulus response en
dc.subject.other stoichiometry en
dc.subject.other Mammalia en
dc.title The logic of EGFR/ErbB signaling: Theoretical properties and analysis of high-throughput data en
heal.type journalArticle en
heal.identifier.primary 10.1371/journal.pcbi.1000438 en
heal.identifier.secondary http://dx.doi.org/10.1371/journal.pcbi.1000438 en
heal.identifier.secondary e1000438 en
heal.language English en
heal.publicationDate 2009 en
heal.abstract The epidermal growth factor receptor (EGFR) signaling pathway is probably the best-studied receptor system in mammalian cells, and it also has become a popular example for employing mathematical modeling to cellular signaling networks. Dynamic models have the highest explanatory and predictive potential; however, the lack of kinetic information restricts current models of EGFR signaling to smaller sub-networks. This work aims to provide a large-scale qualitative model that comprises the main and also the side routes of EGFR/ErbB signaling and that still enables one to derive important functional properties and predictions. Using a recently introduced logical modeling framework, we first examined general topological properties and the qualitative stimulus-response behavior of the network. With species equivalence classes, we introduce a new technique for logical networks that reveals sets of nodes strongly coupled in their behavior. We also analyzed a model variant which explicitly accounts for uncertainties regarding the logical combination of signals in the model. The predictive power of this model is still high, indicating highly redundant sub-structures in the network. Finally, one key advance of this work is the introduction of new techniques for assessing high-throughput data with logical models (and their underlying interaction graph). By employing these techniques for phospho-proteomic data from primary hepatocytes and the HepG2 cell line, we demonstrate that our approach enables one to uncover inconsistencies between experimental results and our current qualitative knowledge and to generate new hypotheses and conclusions. Our results strongly suggest that the Rac/Cdc42 induced p38 and JNK cascades are independent of PI3K in both primary hepatocytes and HepG2. Furthermore, we detected that the activation of JNK in response to neuregulin follows a PI3K-dependent signaling pathway. © 2009 Samaga et al. en
heal.publisher PUBLIC LIBRARY SCIENCE en
heal.journalName PLoS Computational Biology en
dc.identifier.doi 10.1371/journal.pcbi.1000438 en
dc.identifier.isi ISI:000270799700033 en
dc.identifier.volume 5 en
dc.identifier.issue 8 en

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