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dc.contributor.authorDimitrakopoulou, Konstantina
dc.contributor.authorTsimpouris, Charalampos
dc.contributor.authorPapadopoulos, George
dc.contributor.authorPommerenke, Claudia
dc.contributor.authorWilk, Esther
dc.contributor.authorSgarbas, Kyriakos N
dc.contributor.authorSchughart, Klaus
dc.contributor.authorBezerianos, Anastasios
dc.date.accessioned2016-01-20T14:54:04Zen
dc.date.available2016-01-20T14:54:04Zen
dc.date.issued2011en
dc.identifier.citationDynamic gene network reconstruction from gene expression data in mice after influenza A (H1N1) infection. 2011, 1:27 J Clin Bioinformaen
dc.identifier.issn2043-9113en
dc.identifier.pmid22017961en
dc.identifier.doi10.1186/2043-9113-1-27en
dc.identifier.urihttp://hdl.handle.net/10033/594411en
dc.description.abstractThe immune response to viral infection is a temporal process, represented by a dynamic and complex network of gene and protein interactions. Here, we present a reverse engineering strategy aimed at capturing the temporal evolution of the underlying Gene Regulatory Networks (GRN). The proposed approach will be an enabling step towards comprehending the dynamic behavior of gene regulation circuitry and mapping the network structure transitions in response to pathogen stimuli.
dc.language.isoenen
dc.titleDynamic gene network reconstruction from gene expression data in mice after influenza A (H1N1) infection.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Centre for infection research, Inhoffenstr. 7, D-38124 Braunschweig, Germany.en
dc.identifier.journalJournal of clinical bioinformaticsen
refterms.dateFOA2018-06-13T19:56:54Z
html.description.abstractThe immune response to viral infection is a temporal process, represented by a dynamic and complex network of gene and protein interactions. Here, we present a reverse engineering strategy aimed at capturing the temporal evolution of the underlying Gene Regulatory Networks (GRN). The proposed approach will be an enabling step towards comprehending the dynamic behavior of gene regulation circuitry and mapping the network structure transitions in response to pathogen stimuli.


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