Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections

Background: The recent emergence of the H5N1 influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily infect humans. We analyzed differential gene expression of lung epithelial cells to compare the response to H5N1 infection with a more benign infection with Respiratory Syncytial Virus (RSV). These gene expression data are then used as seeds to find important nodes by using a novel combination of the Gene Ontology database and the Human Network of gene interactions. Additional analysis of the data is conducted by training support vector machines (SVM) with the data and examining the orientations of the optimal hyperplanes generated. Results: Analysis of gene clustering in the Gene Ontology shows no significant clustering of genes unique to H5N1 response at 8 hours post infection. At 24 hours post infection, however, a number of significant gene clusters are found for nodes representing "immune response&qu...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Ken Tatebe, Ahmet Zeytun, Ruy M. Ribeiro, Robert Hoffmann, Kevin S. Harrod, Christian V. Forst
• Keywords: BMCBI 2010, Gene, Gene Ontology, H5N1