The vast majority of the diversity of life on Earth is microbial. Microbes have a profound impact on our planet through their roles
in biogeochemical cycling in marine, freshwater and terrestrial environments, and they are essential participants in agriculture and in human
health and disease. Yet we still have only a rudimentary understanding of the evolutionary, physiological, genetic and ecological forces that
generate and maintain microbial diversity, and that govern the interactions of microbes with the rest of the biota. The application of DNA
sequencing technologies to characterize the genomes of a wide diversity of microbes has generated vast quantities of genome sequence data.
Now the intellectual challenge is to develop from this enormous resource more comprehensive and theoretically robust phylogenetic, genetic and
ecological models to further our understanding of the many roles of microbes in the biological world. Thus an overarching research goal of the
Centre for Comparative Genomics and Evolutionary Bioinformatics (CGEB) is to elucidate how genomic and proteomic data from diverse microbes
can best be harnessed to understand the patterns of biodiversity and the evolutionary processes by which this diversity was generated.
The Centre for Comparative Genomics and Evolutionary Bioinformatics (CGEB) at Dalhousie University is committed to furthering these
scientific goals in the Faculties of Medicine, Science and Computer Science. Although microbial diversity is at the heart of many of our
research activities, our work spans computational biology, computer science, statistical modeling and comparative genomics, with a strong
focus on method and theory. We are united by the common goal of using genomic information to elucidate evolutionary patterns and processes:
the pathways by which microbial organisms have diversified over the last 3.5 billion years of Earth's history and through which they continue
to shape the global environment. Only through the integration of experimental genomic approaches and sophisticated bioinformatic modeling will
we be able to achieve this goal.