Predicting the Response to Combination Antiretroviral Therapy: Retrospective Validation of geno2pheno‐THEO on a Large Clinical Database | Zendy

André Altmann | Zendy; Martin Däumer | Zendy; Niko Beerenwinkel | Zendy; Yardena Peres | Zendy; Eugen Schülter | Zendy; Joachim Büch | Zendy; SooYon Rhee | Zendy; Anders Sönnerborg | Zendy; W. Jeffrey Fessel | Zendy; Robert W. Shafer | Zendy; Maurizio Zazzi | Zendy; Rolf Kaiser | Zendy; Thomas Lengauer | Zendy

Open Access

Predicting the Response to Combination Antiretroviral Therapy: Retrospective Validation of geno2pheno‐THEO on a Large Clinical Database

Author(s) -

André Altmann,

Martin Däumer,

Niko Beerenwinkel,

Yardena Peres,

Eugen Schülter,

Joachim Büch,

SooYon Rhee,

Anders Sönnerborg,

W. Jeffrey Fessel,

Robert W. Shafer,

Maurizio Zazzi,

Rolf Kaiser,

Thomas Lengauer

Publication year - 2009

Publication title -

the journal of infectious diseases

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.69

H-Index - 252

eISSN - 1537-6613

pISSN - 0022-1899

DOI - 10.1086/597305

Subject(s) - set (abstract data type) , human immunodeficiency virus (hiv) , wilcoxon signed rank test , antiretroviral therapy , computer science , selection (genetic algorithm) , sequence (biology) , interpretation (philosophy) , task (project management) , artificial intelligence , computational biology , statistics , biology , viral load , virology , mathematics , engineering , genetics , mann–whitney u test , systems engineering , programming language

Expert-based genotypic interpretation systems are standard methods for guiding treatment selection for patients infected with human immunodeficiency virus type 1. We previously introduced the software pipeline geno2pheno-THEO (g2p-THEO), which on the basis of viral sequence predicts the response to treatment with a combination of antiretroviral compounds by applying methods from statistical learning and the estimated potential of the virus to escape from drug pressure.

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