Viruses 2011, 3(5), 613-619; doi:10.3390/v3050613
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Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

1 Department of Microbiology & Immunology, Institute for Human Infections & Immunity, University of Texas Medical Branch, Galveston, TX 77555, USA 2 Center for Biodefense and Emerging Infectious Diseases, Sealy Center for Vaccine Development, University of Texas Medical Branch, Galveston, TX 77555, USA
* Author to whom correspondence should be addressed.
Received: 2 April 2011; Accepted: 20 April 2011 / Published: 12 May 2011
(This article belongs to the Special Issue Pathogenesis of Emerging and Re-Emerging RNA Viruses)
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Abstract: The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.
Keywords: viral hemorrhagic fever; arenavirus; Ebola virus; Rift Valley fever virus; microarray; proteomics; bioinformatics

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MDPI and ACS Style

Bowick, G.C.; McAuley, A.J. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection. Viruses 2011, 3, 613-619.

AMA Style

Bowick GC, McAuley AJ. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection. Viruses. 2011; 3(5):613-619.

Chicago/Turabian Style

Bowick, Gavin C.; McAuley, Alexander J. 2011. "Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection." Viruses 3, no. 5: 613-619.

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