| Autor: |
Lee CC; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan.; Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan.; Genomic Medicine Core Laboratory, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan., Lau YC; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan., Liang YK; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan., Hsian YH; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan., Lin CH; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan., Wu HY; Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan., Tan DJY; Department of Microbiology and Immunology and Division of Microbiology, Graduate Institute of Biomedical Sciences, School of Medicine, Chang Gung University, Taoyuan 333, Taiwan., Yeh YM; Genomic Medicine Core Laboratory, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan., Chao M; Department of Microbiology and Immunology and Division of Microbiology, Graduate Institute of Biomedical Sciences, School of Medicine, Chang Gung University, Taoyuan 333, Taiwan.; Liver Research Center, Department of Hepato-Gastroenterology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan. |
| Abstrakt: |
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. |
