| Literature DB >> 34170311 |
Reema Singh1, Anthony Kusalik2, Jo-Anne R Dillon3.
Abstract
Whole-genome sequencing (WGS) data are well established for the investigation of gonococcal transmission, antimicrobial resistance prediction, population structure determination and population dynamics. A variety of bioinformatics tools, repositories, services and platforms have been applied to manage and analyze Neisseria gonorrhoeae WGS datasets. This review provides an overview of the various bioinformatics approaches and resources used in 105 published studies (as of 30 April 2021). The challenges in the analysis of N. gonorrhoeae WGS datasets, as well as future bioinformatics requirements, are also discussed.Entities:
Keywords: zzm321990 Neisseria gonorrhoeaezzm321990 ; antimicrobial resistance; bioinformatics; molecular epidemiology; population structure; strain typing; whole genome sequencing
Mesh:
Year: 2022 PMID: 34170311 PMCID: PMC9001900 DOI: 10.1093/bfgp/elab028
Source DB: PubMed Journal: Brief Funct Genomics ISSN: 2041-2649 Impact factor: 4.840