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Using machine learning and big data to explore the drug resistance landscape in HIV.
Blassel, Luc; Tostevin, Anna; Villabona-Arenas, Christian Julian; Peeters, Martine; Hué, Stéphane; Gascuel, Olivier.
Affiliation
  • Blassel L; Unité de Bioinformatique Évolutive, Institut Pasteur, Paris, France.
  • Tostevin A; Sorbonne Université, Collège doctoral, Paris, France.
  • Villabona-Arenas CJ; Institute for Global Health, UCL, London, United Kingdom.
  • Peeters M; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Hué S; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Gascuel O; TransVIHMI (Recherches Translationnelles sur VIH et Maladies Infectieuses), Université de Montpellier, Institut de Recherche pour le Développement, INSERM, Montpellier, France.
PLoS Comput Biol ; 17(8): e1008873, 2021 08.
Article in En | MEDLINE | ID: mdl-34437532
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / HIV-1 / Drug Resistance, Viral / Supervised Machine Learning / Big Data Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Africa / Europa Language: En Journal: PLoS Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2021 Document type: Article Affiliation country: France Country of publication: United States
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / HIV-1 / Drug Resistance, Viral / Supervised Machine Learning / Big Data Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Africa / Europa Language: En Journal: PLoS Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2021 Document type: Article Affiliation country: France Country of publication: United States