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Drug resistance mutations in HIV: new bioinformatics approaches and challenges

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  • معلومة اضافية
    • Contributors:
      Bioinformatique évolutive - Evolutionary Bioinformatics; Institut Pasteur Paris (IP)-Centre National de la Recherche Scientifique (CNRS); Collège Doctoral; Sorbonne Université (SU); Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB; Institut Pasteur Paris (IP)-Université Paris Cité (UPCité); London School of Hygiene and Tropical Medicine (LSHTM); The University of Edinburgh; Institut de Systématique, Evolution, Biodiversité (ISYEB); Muséum national d'Histoire naturelle (MNHN)-École Pratique des Hautes Études (EPHE); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA); This work was supported by: Horizon 2020 framework program (Award number 634650, VIROGENESIS project, OG recipient, LB master salary); Agence Nationale de la Recherche (Award number ANR-19-P3IA-0001, PIA3 programme, PRAIRIE project, OG recipient, LB PhD salary); European Research Council (ERC) Starting Grant (Number 757688, awarded to Katherine E. Atkins, KEA and CJVA).; ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019); European Project: 634650,H2020,H2020-PHC-2014-two-stage,VIROGENESIS(2015)
    • بيانات النشر:
      CCSD
      Elsevier
    • الموضوع:
      2021
    • Collection:
      Université des Antilles (UAG): HAL
    • نبذة مختصرة :
      International audience ; Drug resistance mutations appear in HIV under treatment pressure. Resistant variants can be transmitted to treatmentnaive individuals, which can lead to rapid virological failure and can limit treatment options. Consequently, quantifying the prevalence, emergence and transmission of drug resistance is critical to effectively treating patients and to shape health policies. We review recent bioinformatics developments and in particular describe: (1) the machine learning approaches intended to predict and explain the level of resistance of HIV variants from their sequence data; (2) the phylogenetic methods used to survey the emergence and dynamics of resistant HIV transmission clusters; (3) the impact of deep sequencing in studying within-host and between-host genetic diversity of HIV variants, notably regarding minority resistant variants.
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/34597873; info:eu-repo/grantAgreement//634650/EU/Virus discovery and epidemic tracing from high throughput metagenomic sequencing/VIROGENESIS; PUBMED: 34597873
    • الرقم المعرف:
      10.1016/j.coviro.2021.09.009
    • الدخول الالكتروني :
      https://hal.sorbonne-universite.fr/hal-03369954
      https://hal.sorbonne-universite.fr/hal-03369954v1/document
      https://hal.sorbonne-universite.fr/hal-03369954v1/file/1-s2.0-S1879625721001073-main.pdf
      https://doi.org/10.1016/j.coviro.2021.09.009
    • Rights:
      http://creativecommons.org/licenses/by-nc-nd/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.7B9F82C4