Jeffrey L. Thorne

Professor of Genetics and Statistics
North Carolina State University

Office: 1507 Partners II, Centennial Campus
Email: thorne _at_ statgen.ncsu.edu
Phone: (919)515-1946
Fax: (919)515-7315
Other Contact Information
 

Research Group (current)

Reed Cartwright (Postdoctoral Fellow)
Sang Chul Choi (Graduate Student)
Asger Hobolth (Visiting Scientist/Postdoctoral Fellow)
Benjamin Redelings (Postdoctoral Fellow)

Alumni

Stéphane Aris-Brosou  (now at University of Ottawa)
Douglas Robinson (now at Bristol-Myers Squibb Co.)
Betsy Scholl (now in nematode group at N.C. State)
Tae-Kun Seo (now at University of Tokyo)
Jiaye Yu (now at University of Copenhagen)


Research Project 1: Improving models for DNA evolution by incorporating phenotype

The relationship between phenotype and survival of the genotype is central to both genetics and evolution.  A wide variety of computational biology techniques aim to predict aspects of phenotype from DNA sequence data.  We are working to improve models of molecular evolution by incorporating these computational biology prediction systems.  Because phenotype can induce dependence among changes that occur at different positions within a gene sequence, conventional procedures for making evolutionary inferences are not computationally tractable and new statistical procedures are needed. Our recent efforts have concentrated on protein tertiary structure and RNA secondary structure, but we are very excited by the potential to quantify the impacts on evolution of diverse other aspects of phenotype.  Collaborators who have made important contributions to this research include:  David Jones  of University College London,  Hirohisa Kishino of the University of Tokyo, and  Nick Goldman  of the European Bioinformatics Institute.
 

Research Project 2: Evolution of the rate of evolution

Evolutionary analysis of DNA and protein sequences is typically performed by either assuming that all evolutionary lineages change at the same rate or by avoiding any attempt to directly consider the fact that the rate of evolution changes over time. Factors that affect the rate of molecular evolution (e.g., mutation, population size, generation time, selection) change over time and therefore the rate of molecular evolution is extremely unlikely to be identical for different evolutionary lineages. However, it is reasonable to expect an autocorrelation of rates over time. Closely related evolutionary lineages tend to evolve at similar rates and distantly related lineages might evolve at more different rates. Hirohisa Kishino (University of Tokyo), Tae-Kun Seo (University of Tokyo), and I are developing methods for estimating dates of evolutionary events from molecular sequence data without the restrictive and implausible assumption that rates of evolution have been constant over time.  We also feel that these methods have great potential for illuminating patterns of evolutionary rate variation over time.

Our rate evolution and divergence time estimation software is crude, free, and available here.

Teaching

In the fall of every odd-numbered year, I co-teach a course in my own research area. My co-teacher Dr. William Atchley is to blame for the ugly title of the course (Computational Molecular Evolution). The course is actually much better than its name. In recent years, I have also taught Bioinformatics II, a graduate level course that covers methods for analyzing data relevant to molecular biology.
 

Many of my reprints can be found here.

For other information, please see my C.V.

A message from my baby girl for visitors to this page.


Some Other Links: N.C.S.U.  Statistical Genetics and Bioinformatics     N.C.S.U. Genetics N.C.S.U. Statistics   www.theonion.com