The Ohio State University
June 18-August 10, 2012 (8 weeks)
OSU - Department of Mathematics
OSU - Department of Statistics
(interacts with existing UBM program)
Topic 1:
Modeling cholera disease dynamics - Joe Tien
Project Description:
The cholera outbreak beginning in Haiti in October 2010 illustrates the continuing public health concern of this disease. Our group uses a variety of mathematical approaches to model cholera dynamics and assess different intervention strategies. Some of the questions we seek to address using mathematical models include: 1) understanding how human movement patterns influence the spread of cholera, 2) predicting seasonal fluctuations in disease intensity, and understanding the mechanisms underlying this seasonality, 3) investigating the role of "hot spots" in disease invasion and persistence.
Pre-requisites:
Familiarity with ordinary differential equations and computer programming are desirable. Exposure to dynamical systems and statistics would be helpful, but not required.
Topic 2:
Statistical Phylogenetics - Laura Kubatko
Project Description:
Phylogenetic trees are graphs that display ancestry-descent relationships among a set of present-day species. A fundamental goal in evolutionary biology is the inference of a phylogenetic tree given some data, often in the form of DNA sequences, for the species of interest. In this project, students will study the main ideas involved in the estimation of phylogenetic trees from DNA sequence data. They will then apply this knowledge to a real-world DNA sequence data set, with the goal of estimating a phylogenetic tree as well as quantifying the error in the estimate. The estimated phylogeny will then be used to examine questions of interest concerning the organisms under study. Examples of such questions are the directionality of trait evolution, the phylogeographic movement of ancestral populations, the compatibility of molecular and morphological data, or whether speciation has occurred via hybridization.
Pre-requisites:
It will be useful if students have a background in statistics (at the level of an introductory course) and experience with computing (or at least an interest in learning to use different software for phylogenetic estimation). However, motivated students without this type of experience can easily learn everything that is required during the program.
