IN CLARK S360!!
Philip Labo studied both biology and computer science as an undergraduate at Penn. He received his B.A., in biology, in 2004. During that time he also worked as a programmer/analyst for the Plasmodium falciparum genome database (plasmodb.org). Philip left Penn for Stanford in Fall 2005 to pursue a doctorate in statistics. His doctoral research focused on the modeling of adaptive evolution in certain populations of baker’s yeast. He also studied the modeling of adaptive evolution in general. During the Spring of 2011 he started working with Jamie Jones, of the Stanford Anthropology Department, on the analysis of evolutionary pressures on life history patterns in the Utah Population Database. Philip now works as a post-doctoral scholar with the Prematurity Research Center in the Stanford School of Medicine lending his statistical expertise to the study of preterm birth in United States. Jamie Jones and Paul Wise oversee his work.
Talk: Yeast population dynamics: Stopping times and logistic curves
Kao & Sherlock (2008) describes eight experiments with baker’s yeast. Each experiment involves a chemostat, a sugar-limited medium, a numer- ically large baker’s yeast population, and the evolution of said population over nearly five hundred generations. The output from these experiments lead us to consider the Wright-Fisher and Moran models of population ge- netics lore (Fisher (1922); Wright (1931); Moran (1958)). How might we expect these populations to behave if under the influence of such simple underlying dynamics? We study expected stopping times and expected path functions, reviewing old results and deriving new. We also provide a loose demonstration of our efforts to fit said models to the data from Kao & Sherlock (2008). While these relatively simple models may “fit” these data, this does not suggest that these simple dynamics actually obtain in real life (see for example Desai & Fisher (2007)).
Wednesday May 14th, 2014
1:15 PM Seminar
Location: Clark S360!!