Journal of Hematology & Thromboembolic Diseases
Open Access

Valeria Cento

Publications

• Research Article
  Using Bayesian Models to Locate Mutations for HBV Drug Resistance
  Author(s): Gadareth Higgs, Zhixiang Lin, Valeria Cento Valentina Svicher, Shilpa Hattangadi, Jing ZhangGadareth Higgs, Zhixiang Lin, Valeria Cento Valentina Svicher, Shilpa Hattangadi, Jing Zhang
  
  Introduction: The Hepatitis B virus (HBV) is very common, and has been difficult to treat, mainly because of the high mutation rate of the polymerase gene of its reverse transcriptase. The aim of our study was to use Bayesian statistics to determine the positions of mutations within the HBV genome. Material and methods: The sequence data was derived from 73-treatment naïve and 215 treatment failures, of various drugs, from patient data provided by collaborators at the University of Tor Vergata. The Metropolis-Hastings algorithm was applied to the data to determine the mutation locations that correlate with drug resistance. Results: For amino acid positions 80-250, nineteen positions were shown to have mutated in the treatment failure group. Fifteen of the nineteen positions were in the D genotype of HBV, while.. View More»
  DOI: 10.4172/2329-8790.1000166

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