Historically, the study of microbes and their taxonomical classification has achieved after a painstakingly process of phenotypic and genetic characterization. This classification schema is been confronted with new challenges as genomic information began to accumulate in public databases and discrepancies with phenotypical information began to accumulate. The above situation is complicated because the short replication times and high mutation rates that allows pathogens to overcome immunological pressures, widen their host range and geographical distribution. This is limiting our understanding of pathogen adaptation, divergence and epidemiological patterns.

The short replication times and high substitution rates that allow bacterial and viral hemorrhagic viruses to overcome host immunological pressures and to widen their host range, has restricted the isolation of genome segments that can be associated with geographical distribution, pathogenesis, and replication dynamics. To address these limitations, my group is developing a motif fingerprint and genomic barcoding algorithms for determining the percentage of a pathogen genome that remains species specific. Our work has yielded a Comparative Agreement Search Tools that outperforms classical bioinformatics sequence homology tools. Our benchmarking and extensive computational survey using of all sequence information publicly available (genomic and metagenomic data sets) has also differentiated a set of genus-specific amino acid sequences that formed binary patterns across the genome of species and strains.

To store this information we developed and integrated management system that allows the classification of known and unknown microbes and the selection of broad spectrum therapeutic targets. Genomic signatures and barcodes are been incorporated in detection devices and in the rational development of therapetuic countermeasures.