HIV multidrug class resistance prediction with a time sliding anchor approach.

Journal: Bioinformatics advances
Published Date: Jan 1, 2025

Abstract

MOTIVATION: The emergence of multidrug class resistance (MDR) in Human Immunodeficiency Virus (HIV) is a rare but significant challenge in antiretroviral therapy (ART). MDR, which may arise from prolonged drug exposure, treatment failures, or transmission of resistant strains, accelerates disease progression and poses particular challenges in resource-limited settings with restricted access to resistance testing and advanced therapies. Early prediction of future MDR development is important to inform therapeutic decisions and mitigate its occurrence.

Authors

  • Nurhan Arslan
    Department of Computer Science, Methods in Medical Informatics, University of Tuebingen, Tübingen, Germany.
  • Ralf Eggeling
    Department of Informatics, Methods in Medical Informatics, Eberhard Karls University of Tübingen Faculty of Mathematics and Natural Sciences, Tubingen, Germany.
  • Bernhard Reuter
    Methods in Medical Informatics, Department of Computer Science, University of Tübingen, Tübingen 72076, Germany.
  • Kristel Van Leathem
    Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven 3000, Belgium.
  • Marta Pingarilho
    Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, Lisbon 1349-008, Portugal.
  • Perpétua Gomes
    Laboratório de Biologia Molecular, LMCBM, SPC, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, Caparica 2829-511, Portugal.
  • Anders Sönnerborg
    Karolinska Institutet, Stockholm, Sweden.
  • Rolf Kaiser
    Institute for Virology, University of Cologne, Fürst-Pückler-Str. 56, 50935, Cologne, Germany.
  • Maurizio Zazzi
  • Nico Pfeifer
    Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken and Saarbrücken Graduate School of Computer Science, Saarland University, 66123 Saarbrücken.

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