Title of article
Boolean Modeling of Cellular and Molecular Pathways Involved in Influenza Infection
Author/Authors
Anderson, Christopher S Department of Microbiology and Immunology - University of Rochester Medical Center - Rochester, USA , DeDiego, Marta L Department of Microbiology and Immunology - University of Rochester Medical Center - Rochester, USA , Topham, David J Department of Microbiology and Immunology - University of Rochester Medical Center - Rochester, USA , Thakar, Juilee Department of Microbiology and Immunology - University of Rochester Medical Center - Rochester, USA
Pages
11
From page
1
To page
11
Abstract
Systems virology integrates host-directed approaches with molecular profiling to understand viral pathogenesis. Self-contained
statistical approaches that combine expression profiles of genes with the available databases defining the genes involved in the
pathways (gene-sets) have allowed characterization of predictive gene-signatures associated with outcome of the influenza virus
(IV) infection. However, such enrichment techniques do not take into account interactions among pathways that are responsible
for the IV infection pathogenesis. We investigate dendritic cell response to seasonal H1N1 influenza A/New Caledonia/20/1999
(NC) infection and infer the Boolean logic rules underlying the interaction network of ligand induced signaling pathways and
transcription factors. The model reveals several novel regulatory modes and provides insights into mechanism of cross talk between
NF𝜅B and IRF mediated signaling. Additionally, the logic rule underlying the regulation of IL2 pathway that was predicted by the
Boolean model was experimentally validated. Thus, the model developed in this paper integrates pathway analysis tools with the
dynamic modeling approaches to reveal the regulation between signaling pathways and transcription factors using genome-wide
transcriptional profiles measured upon influenza infection.
Keywords
Boolean , Molecular , Cellular
Journal title
Computational and Mathematical Methods in Medicine
Serial Year
2016
Full Text URL
Record number
2607388
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