Statistically Predicting Hotspots and Coldspots in Caenorhabditis Elegans

University Of New Hampshire, Durham NH

Investigators

Abstract

The Principal Investigator, whose background is in statistics, will spend a year immersed in genomics research at the Hubbard Center for Genome Studies (HCGS) at the University of New Hampshire. She will focus her studies on comparative genomics using the model nematode, Caenorhabditis elegans. The PI will become involved in the ongoing analysis of mutations in C. elegans, specifically developing statistical models for predicting the types of mutations that will occur. This analysis will be based on the comparison of the laboratory strain of C. elegans with other strains and closely related species. The statistical models will initially focus on the prediction of cold spots, DNA sequences in the genome with low rates of mutation and hot spots, DNA sequences in the genome with high mutation rates. She plans to use Markov Chain methods, multiple comparisons and nonparametric methods, Bayesian methods, and linkage analysis to find the statistical methods of predictions. During this year of immersion in genomic analysis, the PI will engage colleagues and students at the HCGS as an active member of the informatics group to develop her knowledge base in genomics. The PI will gain genomics experience, which when combined with her statistical knowledge, will aid in establishing long-term fruitful collaborations and in planning future research directions. The PI plans to enrich the educational experiences of students in several ways: (1) organize statistical workshops held at the HCGS, (2) assist in the design a new MBA Management of Biotechnology specialization for Part-Time students at her home school, and (3) help recruit genomics and computer science students to a newly designed one-year Full Time MBA program. In this way, the career options of non-business students would be expanded by making them more qualified for managerial positions. This IGMS project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).