  For nearly 50 years microbiologists have been determining prokaryotic genome
relatedness by means of nucleic acid reassociation kinetics. These methods,
however, are technically challenging, difficult to reproduce, and - given the
time and resources it takes to generate a single data-point - not cost
effective. In the post genomic era, with the cost of sequencing whole
prokaryotic genomes no longer a limiting factor, we believed that
computationally predicting the output value from a traditional DNA-DNA
hybridization experiment using pair-wise comparisons of whole genome sequences
to be of value. While other computational whole-genome classification methods
exist, they predict values on widely different scales than DNA-DNA
hybridization, introducing yet another metric into the polyphasic approach of
defining microbial species. Our goal was to develop an in silico BLAST based
pipeline that would predict with a high level of certainty the value of the wet
lab-based DNA-DNA hybridization values. Here we report on one such method that
produces estimates that are both accurate and precise with respect to the
DNA-DNA hybridization values they are designed to emulate.
