Postdoctoral Research Fellowships in Biology for FY 2009

Brown Jeremy M, Austin TX

Investigators

Abstract

This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "New Statistical Approaches to Inferring Phylogenies with Genomic Data" for Jeremy Brown. The host institution for this research is the University of California - Berkeley and the sponsoring scientist is John Huelsenbeck. DNA sequence data are being gathered at an extraordinary pace, which offers a wealth of new information for inferring the evolutionary relationships (phylogenies) between living things. Understanding these relationships is crucial both in answering basic biological questions about organismal evolution and for a number of applied problems related to human health and well-being (e.g., infectious disease transmission and biodiversity conservation). However, the problem of inferring phylogenies with such massive data sets presents unique analytical challenges. This research develops new statistical approaches to analyze genomic data with more accuracy and efficiency. In particular, this research designs new models of DNA sequence evolution that are able to flexibly incorporate variation in evolutionary forces such as mutation, selection, and drift, which can be markedly different across genes. This research also develops metrics for assessing when statistical methods are likely to be misleading and return incorrect phylogenetic estimates. The training objectives of this work include the development of skills at the intersection of statistics, computer science, genetics, bioinformatics, and organismal biology. Such an interdisciplinary view is essential to solving longstanding, important problems in biology with the new flood of genomic data. Expected are improved methods of analysis that are used in thousands of studies per year, resulting in better answers to a range of important biological questions.