Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon

James Lara; John E. Tavis; Maureen J. Donlin; William M. Lee; He Jun Yuan; Brian L. Pearlman; Gilberto Vaughan; Joseph C. Forbi; Guo Liang Xia; Yury E. Khudyakov

doi:10.3233/ISB-2012-0456

Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon

James Lara, John E. Tavis, Maureen J. Donlin, William M. Lee, He Jun Yuan, Brian L. Pearlman, Gilberto Vaughan, Joseph C. Forbi, Guo Liang Xia, Yury E. Khudyakov

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.

Original language	English (US)
Pages (from-to)	213-224
Number of pages	12
Journal	In Silico Biology
Volume	11
Issue number	5
DOIs	https://doi.org/10.3233/ISB-2012-0456
State	Published - 2012

ASJC Scopus subject areas

Molecular Biology
Genetics
Computational Mathematics
Computational Theory and Mathematics

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title = "Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon",

abstract = "Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.",

author = "James Lara and Tavis, {John E.} and Donlin, {Maureen J.} and Lee, {William M.} and Yuan, {He Jun} and Pearlman, {Brian L.} and Gilberto Vaughan and Forbi, {Joseph C.} and Xia, {Guo Liang} and Khudyakov, {Yury E.}",

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TY - JOUR

T1 - Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon

AU - Lara, James

AU - Tavis, John E.

AU - Donlin, Maureen J.

AU - Lee, William M.

AU - Yuan, He Jun

AU - Pearlman, Brian L.

AU - Vaughan, Gilberto

AU - Forbi, Joseph C.

AU - Xia, Guo Liang

AU - Khudyakov, Yury E.

PY - 2012

Y1 - 2012

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AB - Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.

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Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon

Abstract

ASJC Scopus subject areas

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