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= Recent News = | = Recent News = | ||
== 04/22/2011—Contact | == 04/01/2012—Matthew Tien wins NSF Graduate Research Fellowship == | ||
Matthew Tien, an undergraduate researcher currently working in the Wilke lab, has been awarded an NSF Graduate Research Fellowship in this year's competition. For his graduate work, Matthew will be joining [http://drummond.openwetware.org/ Allan Drummond's laboratory] at the University of Chicago. Matthew plans to use mass spectrometry to investigate the world of mistranslated and misfolded proteins. | |||
== 04/22/2011—Contact networks shape parasite evolutionary trees == | |||
[[Image:Wilke_newsicon_04222011.png|left|150px]] The inference of population dynamics (such as the number of infected individuals as a function of time) from molecular sequence data is becoming an important new method for the surveillance of infectious diseases. We have examined how heterogeneity in host contacts shapes the genealogies of parasitic agents. We find that contact heterogeneity can have a strong effect on how the structure of genealogies reflects epidemiologically relevant quantities such as the proportion of a population that is infected. Contact heterogeneity also can increase the number of sequence isolates required to estimate these quantities over the course of an epidemic. Our results suggest that data about contact-network structure will be required in addition to sequence data for accurate estimation of a parasitic agent's genealogy. This work is published in a special issue of the journal Perspectives on Infectious Diseases focused on [http://www.hindawi.com/journals/ipid/2011/238743/ network perspectives on infectious disease dynamics]. | [[Image:Wilke_newsicon_04222011.png|left|150px]] The inference of population dynamics (such as the number of infected individuals as a function of time) from molecular sequence data is becoming an important new method for the surveillance of infectious diseases. We have examined how heterogeneity in host contacts shapes the genealogies of parasitic agents. We find that contact heterogeneity can have a strong effect on how the structure of genealogies reflects epidemiologically relevant quantities such as the proportion of a population that is infected. Contact heterogeneity also can increase the number of sequence isolates required to estimate these quantities over the course of an epidemic. Our results suggest that data about contact-network structure will be required in addition to sequence data for accurate estimation of a parasitic agent's genealogy. This work is published in a special issue of the journal Perspectives on Infectious Diseases focused on [http://www.hindawi.com/journals/ipid/2011/238743/ network perspectives on infectious disease dynamics]. | ||
