Data Mining on DNA Sequences of Hepatitis B Virus

: Extraction of meaningful information from large experimental datasets is a key element of 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. In this study, a data mining framework which includes molecular evolution analysis, clustering, feature selection, classifier learning and classification, is introduced. In the molecular evolution analysis and clustering, two subgroups have been identified in genotype C and a clustering method has been developed to separate the subgroups. In the feature selection process, potential markers are selected for further classifier learning by Information Gain Theory. Then meaningful rules are learned by the Rule learning with Evolutionary Algorithm classification method. Also, a new classification method by Nonlinear Integral has been developed. Good ...

• Type: Journal
• Year: 2011
• Where: TCBB
• Authors: Kwong-Sak Leung, Kin-Hong Lee, Jin Feng Wang, Eddie Y. T. Ng, Henry L. Y. Chan, Stephen Kwok-Wing Tsui, Tony S. K. Mok, Pete Chi-Hang Tse, Joseph J. Y. Sung
• Keywords: Classification Methods, Liver Cancer, Molecular Evolution Analysis, Software Engineering, TCBB 2011