Computational analysis of molecular sequence data is a key component in solving three critical biological problems of the 21st century: how genes interact to produce living cells, how gene malfunction causes disease and how complex, multicellular organisms evolved from simple, unicellular organisms. In my research, I use computational approaches to studying the role of gene duplication in the acquisition of new gene function and the evolution of vertebrate genomes. New genes arise through gene duplications, errors during cell division that result in extra copies of genes. These extra copies subsequently mutate to take on new functional roles in the cell. The duplication of large regions, ranging from chromosomal segments to the entire genome, is believed to have played a crucial role in early vertebrate evolution. According to the hypothesis, the new genes that resulted from these massive duplications are responsible for the evolution of innovations, such as skeletal structure, limbs, and a complex central nervous system, that distinguish vertebrates from other life forms. If we can understand how these genes acquired new function following duplication, we will have a better understanding of how we evolved and the role those genes play in vertebrates living today.

Durand D, Halldorsson BV, Vernot B. A Hybrid Micro-Macroevolutionary Approach to Gene Tree Reconstruction. J Comput Biol. 2006 Mar;13(2):320-35.

Przytycka T, Davis GB, Song N, Durand D. Graph Theoretical Insights into Evolution of Multidomain Proteins. J Comput Biol. 2006 Mar;13(2):351-63.

Durand D, Hoberman R. Diagnosing duplications--can it be done? Trends Genet. 2006 Mar;22(3):156-64.

Durand D, Sankoff D. Tests for Gene Clustering. Journal of Computational Biology 2003; 10 (3/4): 453-482.

Durand D, Ardlie K, Buttel L, Levin SA, and Silver LM. Impact of Migration and Fitness on the Stability of a Lethal t-haplotype Polymorphism in House Mice: A Computer Study; Genetics 145, Apr. 1997, 1093-1108.