Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Rapid low-cost whole-genome sequencing (WGS) is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data. Here, investigations of the genus Neisseria illustrated the gene-by-gene conceptual approach to the organization and analysis of WGS data. Using the gene and its link to phenotype as a starting point, the BIGSdb database, which powers the PubMLST databases, enables the assembly of large open-access collections of annotated genomes that provide insight into the evolution of the Neisseria, the epidemiology of meningococcal and gonococcal disease, and mechanisms of Neisseria pathogenicity.

Original publication




Journal article


J Clin Microbiol

Publication Date





1949 - 1955


Computational Biology, Genomics, Gonorrhea, High-Throughput Nucleotide Sequencing, Humans, Meningococcal Infections, Neisseria