Statistical methods for studying molecular evolutionary genetics
Various statistical methods are required to analyze and interpret data on molecular evolution. One of my research projects focuses on developing such methods. We are working on methods for inferring phylogenetic trees from various molecular data and estimating the number of nucleotide or amino acid substitutions between different sequences. We are also studying statistical methods for interning the extent of functional differentiation of duplicate genes.

Evolutionary studies of Genomic sequence data
Genomic sequence data provide important information on the evolution of genes and phenotypic characters. Currently we are studying the molecular basis of evolution of morphological and physiological characters such as olfaction and other sensory systems in  vertebrates and flower development in plants. Our approach is to compile genomic gene sequences from various model organisms and to study how the DNA sequences, number of genes involved and the interaction of component multigene families has changed in the evolutionary process. The genetic systems we are studying now include the sensory systems and immune systems  in vertebrates and the flowering system (MADS-box genes) in plants.

Human evolution at the molecular level
To understand the process and pattern of human evolution, we are studying the genetic relationships of various human populations at the molecular level. For this purpose, we have collected allele frequency data for a large number of electrophoretic, immunological, and DNA marker loci. Using these data and statistical methods we developed, we are trying to reconstruct the evolutionary history of human populations.