The Compositive Analysis of Two-component Regulatory Systems in Bacterial Genome

Abstract

Most bacteria adapt to their surroundings by means of "two-component regulatory sys- tems". Bacterial infections remain one of the leading causes of morbidity and mortal- ity of humans in the world. The investi- gation of two-component regulatory systems would greatly contribute to the understand- ing of bacterial physiology and pathogenesis. A two-component regulatory system is com- posed of several functional domains. Pro¯le hidden Markov models are probably the most popular application of hidden Markov models in molecular biology at the moment. By ap- plying pro¯le HMMs technology, we propose methods to report and recognize the posi- tions and types of two-component regulatory systems in bacterial genomes by constructing and integrating similarity scores and Bayesian posterior probabilities of functional domains.