In this talk I will present two different applications of comparative genomics. In the first application we use comparison of complete microbial genomes to reveal a large number of conserved gene clusters - sets of genes that have the same order in two or more different genomes. Such gene clusters often, but not always represent a co-transcribed unit, or operon. Given the enormous quantities of data involved, an efficient computational method for operon prediction based on comparative analyses should not only be highly accurate but also have a fast running time.
In the second application we propose a theoretically novel approach based on a measure called variation of information. Our method assumes a neutral phylogenetic model of evolution, and uses the variation of information criterion to determine regions where the observed mutational rates are higher or lower than expected, allowing us to discover regions under positive or negative selection on any lineage in the phylogeny.