Bioinformatics methods for the analysis of hepatitis viruses

Area of Science:

• Virology
• Bioinformatics
• Hepatology

Background:

• Hepatotropic viruses Hepatitis B (HBV) and Hepatitis C (HCV) cause chronic infections in over 500 million people worldwide.
• Chronic HBV and HCV infections elevate the risk of severe liver complications, including cirrhosis and hepatocellular carcinoma.
• Recent advancements include immune-modulatory drugs and nucleoside/nucleotide analogues for treating HBV and HCV.

Purpose of the Study:

• To review public bioinformatics databases developed for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) research.
• To highlight the integration of bioinformatics tools within these specialized databases for viral genome analysis and drug resistance prediction.

Main Methods:

• Overview of publicly available bioinformatics tools for viral sequence analysis (e.g., ORF identification, gene prediction, homology searching, alignment, motif/epitope recognition).
• Review of specialized database systems designed for HBV and HCV research, focusing on their functionalities and data types.

Main Results:

• Development of public databases specifically for HBV and HCV research, offering tools for genome analysis and drug resistance prediction.
• These databases serve as repositories for viral sequences and provide integrated bioinformatics functionalities.

Conclusions:

• Public databases integrating bioinformatics tools have significant potential to advance hepatitis research and treatment strategies.
• The full impact relies on comprehensive data collection, including molecular sequences and anonymized patient clinical/treatment data.