Bacterial diversity has always been associated with micro-evolutionary events such as horizontal gene transfer and DNA mutations. Such events influence the rapid evolution of bacteria as a result of the environmental conditions which they encounter. They further establish beneficial phenotypic effects that allow bacteria to specialize in new habitats. Due to the increase in number of bacterial genomic sequences, studying microbial evolution has been made possible, and the impact of micro-evolution on bacterial diversity is becoming more apparent. To gain biological information from this ever increasing genomic data, a variety of computational tools are required. This thesis therefore, focuses on the development and application of computational approaches to identify genomic regions of divergence which have resulted from horizontal gene transfer or small mutational changes. The first and major part of the thesis describes the application of DNA patterns, termed oligonucleotide signatures to identify horizontally acquired genomic regions in prokaryotes. These DNA patterns are demonstrated to differentiate between signatures of the core genome and those which have been acquired through horizontal transfer events. DNA patterns are further demonstrated to: reveal the distribution patterns of horizontally acquired genomic elements, determine their acquisition periods, and predict their putative donor organisms. The second part of the thesis focuses on the evaluation of modern short read sequence data of geographically unrelated Pseudomonas aeruginosa to study their intraclonal genomic diversity. The work described in the thesis was purely in silico driven and performed at Hannover Medical School and the Bioinformatics and Computation Biology Unit at the University of Pretoria.