title: Specialized hidden markov model databases for microbial genomics.
abstract: As hidden Markov models (HMMs) become increasingly more important in the analysis of biological sequences, so too have databases of HMMs expanded in size, number and importance. While the standard paradigm a short while ago was the analysis of one or a few sequences at a time, it has now become standard procedure to submit an entire microbial genome. In the future, it will be common to submit large groups of completed genomes to run simultaneously against a dozen public databases and any number of internally developed targets. This paper looks at some of the readily available HMM (or HMM-like) algorithms and several publicly available HMM databases, and outlines methods by which the reader may develop custom HMM targets.
authors.affiliation: University of Nevada, Reno 1664 N. Virginia Street Reno NV 89557-0014 USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Gollery