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Open Access

Investigating Genotype 1a HCV Drug Resistance in NS5A Region via Bayesian Inference

Bina Technologies, Roche, Redwood City, CA 94065, USA.
financial service industry.
Department of Mathematics & Statistics, Georgia State University, Atlanta, GA 30303, USA.
Department of Statistics, Yale University, New Haven, CT 06520.
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Abstract

Hepatitis C virus (HCV) treatment is on the cutting edge of medicine. Due to the high rate of mutations and low fidelity of HCV replication, resistant strains quickly become dominant in a viral population under the selection pressure of a drug. In this paper, we examined the drug resistance mechanism in the NS5A region of genotype 1a HCV virus by comparing the sequence data from interferon-ribavirin treated and untreated patients. To find the drug resistance difference, we used innovative Bayesian probability models to detect mutation combinations and inferred detailed interaction structures of these mutations. We aim to provide reference to drug design and mutation mechanism understanding through our work.

Keywords

Bayesian modelHepatitis C virus (HCV)drug resistanceNS5A

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Tsinghua Science and Technology
Volume 20 Issue 5,
October 2015
Pages 484-490
DOI: 10.1109/TST.2015.7297747
Cite this article:
Fu Y, Chen G, Fu L, et al. Investigating Genotype 1a HCV Drug Resistance in NS5A Region via Bayesian Inference. Tsinghua Science and Technology, 2015, 20(5): 484-490. https://doi.org/10.1109/TST.2015.7297747

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Received: 25 July 2015
Accepted: 06 August 2015
Published: 13 October 2015
The author(s) 2015
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