Data mining on DNA sequences of hepatitis B virus.

Extraction of meaningful information from large experimental data sets is a key element in bioinformatics research. One of the challenges is to identify genomic markers in Hepatitis B Virus (HBV) that are associated with HCC (liver cancer) development by comparing the complete genomic sequences of HBV among patients with HCC and those without HCC. In this study, a data mining framework, which includes molecular evolution analysis, clustering, feature selection, classifier learning, and classification, is introduced.

Genotype-specific genomic markers associated with primary hepatomas, based on complete genomic sequencing of hepatitis B virus.

We aimed to identify genomic markers in hepatitis B virus (HBV) that are associated with hepatocellular carcinoma (HCC) development by comparing the complete genomic sequences of HBVs among patients with HCC and those without. One hundred patients with HBV-related HCC and 100 age-matched HBV-infected non-HCC patients (controls) were studied. HBV DNA from serum was directly sequenced to study the whole viral genome.

Epidemiological and virological characteristics of 2 subgroups of hepatitis B virus genotype C.

Background: We aimed to investigate the characteristics of hepatitis B virus (HBV) genotype C subgroups in Hong Kong and their relationship with HBV genotype C in other parts of Asia.

Methods: Full-genome nucleotide sequences of 49 HBV genotype C isolates from Chinese patients with chronic hepatitis B were compared with the sequences of 69 HBV genotype C isolates and 12 non-genotype C isolates in the GenBank database. Phylogenetic analysis was performed to define the subgroups of HBV genotype C on the basis of >4% heterogeneity of the entire HBV genome.