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WIREs Syst Biol Med
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Influenza A virus infection kinetics: quantitative data and models

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Influenza A virus is an important respiratory pathogen that poses a considerable threat to public health each year during seasonal epidemics and even more so when a pandemic strain emerges. Understanding the mechanisms involved in controlling an influenza infection within a host is important and could result in new and effective treatment strategies. Kinetic models of influenza viral growth and decay can summarize data and evaluate the biological parameters governing interactions between the virus and the host. Here we discuss recent viral kinetic models for influenza. We show how these models have been used to provide insight into influenza pathogenesis and treatment, and we highlight the challenges of viral kinetic analysis, including accurate model formulation, estimation of important parameters, and the collection of detailed data sets that measure multiple variables simultaneously. WIREs Syst Biol Med 2011 3 429–445 DOI: 10.1002/wsbm.129

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Figure 1.

Schematic diagram of the viral dynamics models. (a) Classic model of viral dynamics. Target cells (T) are supplied at constant rate s and die at rate d per day. These cells become infected at rate βV per day. Free virions are produced from infected cells (I) at a rate p and are removed at a rate c. Infected cells are lost at a rate δ. (b) Acute virus infection model modified from the classic model. Target cell regeneration and death are not included. Infected cells were split into two classes, I1 and I2, where virus production initially undergoes an eclipse phase (k).

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Alex Hoffmann

Alex Hoffmann

Dr. Hoffmann is Associate Professor of Signaling Systems Laboratory at UCSD. He moved to biology, tempted by the sense of discovery that he felt was missing as an undergraduate in Physics. During his graduate studies with Dr. Bob Roeder, he identified the genes that make up the transcription factor TFIID. Later on with Dr. David Baltimore, he sought to understand dynamic signaling pathways, realizing that his mathematical background may be relevant to study problems in a quantitative manner.

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