Comparison of Classifier Fusion Methods for Predicting Response to Anti HIV-1 Therapy

• André Altmann ,

  * E-mail: altmann@mpi-inf.mpg.de

  Affiliation Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany

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• Michal Rosen-Zvi,

  Affiliation Machine Learning Group, IBM Research Laboratory in Haifa, Haifa, Israel

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• Mattia Prosperi,

  Affiliation Department of Computer Science and Automation, University of Roma TRE, Rome, Italy

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• Ehud Aharoni,

  Affiliation Machine Learning Group, IBM Research Laboratory in Haifa, Haifa, Israel

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• Hani Neuvirth,

  Affiliation Machine Learning Group, IBM Research Laboratory in Haifa, Haifa, Israel

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• Eugen Schülter,

  Affiliation Institute of Virology, University of Cologne, Cologne, Germany

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• Joachim Büch,

  Affiliation Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany

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• Daniel Struck,

  Affiliation Retrovirology Laboratory, CRP-Santé, Luxembourg, Luxembourg

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• Yardena Peres,

  Affiliation Health Care and Life Sciences Group, IBM Research Laboratory in Haifa, Haifa, Israel

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• Francesca Incardona,

  Affiliation Informa srl, Rome, Italy

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• Anders Sönnerborg,

  Affiliation Division of Infectious Diseases, Department of Medicine, Karolinska Institute, Stockholm, Sweden

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• Rolf Kaiser,

  Affiliation Institute of Virology, University of Cologne, Cologne, Germany

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• Maurizio Zazzi,

  Affiliation Department of Molecular Biology, University of Siena, Siena, Italy

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• Thomas Lengauer

  Affiliation Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany

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