vHDvDB 2.0: Database and Group Comparison Server for Hepatitis Delta Virus
Chi-Ching Lee,
Yiu Chung Lau,
You-Kai Liang,
Yun-Hsuan Hsian,
Chun-Hsiang Lin,
Hsin-Ying Wu,
Deborah Jing Yi Tan,
Yuan-Ming Yeh,
Mei Chao
Affiliations
Chi-Ching Lee
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
Yiu Chung Lau
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
You-Kai Liang
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
Yun-Hsuan Hsian
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
Chun-Hsiang Lin
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
Hsin-Ying Wu
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
Deborah Jing Yi Tan
Department of Microbiology and Immunology and Division of Microbiology, Graduate Institute of Biomedical Sciences, School of Medicine, Chang Gung University, Taoyuan 333, Taiwan
Yuan-Ming Yeh
Genomic Medicine Core Laboratory, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan
Mei Chao
Department of Microbiology and Immunology and Division of Microbiology, Graduate Institute of Biomedical Sciences, School of Medicine, Chang Gung University, Taoyuan 333, Taiwan
The hepatitis delta virus (HDV) is a unique pathogen with significant global health implications, affecting individuals who are coinfected with the hepatitis B virus (HBV). HDV infection has profound clinical consequences, manifesting either as coinfection with HBV, resulting in acute hepatitis and potential liver failure, or as superinfection in chronic HBV cases, substantially increasing the risk of cirrhosis and hepatocellular carcinoma. Given the complex dynamics of HDV infection and the urgent need for advanced research tools, this article introduces vHDvDB 2.0, a comprehensive HDV full-length sequence database. This innovative platform integrates data preprocessing, secondary structure prediction, and epidemiological research tools. The primary goal of vHDvDB 2.0 is to consolidate HDV sequence data into a user-friendly repository, thereby facilitating access for researchers and enhancing the broader scientific understanding of HDV. The significance of this database lies in its potential to streamline HDV research by providing a centralized resource for analyzing viral sequences and exploring genotype-specific characteristics. It will also enable more in-depth research within the HDV sequence domains.
