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Bioinformatics methods for the analysis of hepatitis viruses

Francesco Moriconi, Michael R Beard, Lilly KW Yuen

Corresponding author name: Lilly KW Yuen
Corresponding author e-mail: lilly.yuen@mh.org.au

Citation: Antiviral Therapy 2013; 18:531-539
doi: 10.3851/IMP2613

Date accepted: 18 December 2012
Date published online: 21 June 2013


HBV and HCV are the only hepatotropic viruses capable of establishing chronic infections. More than 500 million people worldwide are estimated to have chronic infections with HBV and/or HCV, and they have an increased risk of developing liver complications, such as cirrhosis or hepatocellular carcinoma. During the past decade, several antiviral agents including immune-modulatory drugs and nucleoside/nucleotide analogues have been approved for the treatment of HBV and HCV infections. In recent years, the focus has been on the development of new and better therapeutic agents for management of chronic HCV infections. Bioinformatics has only been applied recently to the field of viral hepatitis research. In addition to the wide range of general tools freely available for identification of open reading frames, gene prediction, homology searching, sequence alignment, and motif and epitope recognition, several public database systems designed specifically for HBV and HCV research have now been developed. The focus of these databases ranged from being viral sequence repositories for the provision of bioinformatics tools for viral genome analysis, as well as HBV or HCV drug resistance prediction. This review provides an overview of these public databases, which have integrated bioinformatics tools for HBV and HCV research. Properly managed and developed, these databases have the potential to have a broad effect on hepatitis research and treatment strategies. However, the effect will depend on the comprehensive collection of not only molecular sequence data, but also anonymous patient clinical and treatment data.


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