Detection of viruses via statistical gene expression analysis

Minhua Chen, David Carlson, Aimee Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Alfred Hero, Joseph Lucas, Lawrence Carin

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


We develop a new Bayesian construction of the elastic net (ENet), with variational Bayesian analysis. This modeling framework is motivated by analysis of gene expression data for viruses, with a focus on H3N2 and H1N1 influenza, as well as Rhino virus and RSV (respiratory syncytial virus). Our objective is to understand the biological pathways responsible for the host response to such viruses, with the ultimate objective of developing a clinical test to distinguish subjects infected by such viruses from subjects with other symptom causes (e.g., bacteria). In addition to analyzing these new datasets, we provide a detailed analysis of the Bayesian ENet and compare it to related models. © 2006 IEEE.
Original languageEnglish (US)
Pages (from-to)468-479
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Issue number3 PART 1
StatePublished - Mar 1 2011
Externally publishedYes


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