PNNL

Abstract

The human oral microbiome is a complex site containing many hundreds of species with the community response of this microbiome having a large effect on human health. The complexity of this site has spoken to the need for applying –omics techniques to better understand which microbial species are present, their contribution to the microbiome and how this may change as a function of disease. The kinds of datasets that emerge from these –omics studies require computational analysis to gain robust results. New research has also been focused on applying these methods to build computational networks and models that better describe the myriad of interactions between microbial species of the oral cavity and how this changes as a result of infection. I describe in this review the state of the field at this point, what kinds of computational networks have been inferred and what they show. I also describe where the field is heading in the next few years and how more in depth –omics analysis can lead to more detailed models of interactions at this site and improve human health.