HIV multidrug class resistance prediction with a time sliding anchor approach
All analysis was performed using the Euresist Integrated DataBase (EIDB). Researchers wishing to reproduce, validate or extend these findings can request access to the latest EIDB release via the Euresist Network.
Authors
- Maurizio Zazzi (ORCID: https://orcid.org/0000-0002-0344-6281)
- Perpétua Gómes (ORCID: https://orcid.org/0000-0003-3271-8255)
- Nur Arslan
- Kristel Van Laethem (ORCID: https://orcid.org/0000-0001-6036-2271)
- Anders Sönnerborg (ORCID: https://orcid.org/0000-0001-8928-3374)
- Bernhard Reuter (ORCID: https://orcid.org/0000-0002-1617-6778)
- Ralf Eggeling (ORCID: https://orcid.org/0000-0002-3583-1029)
- Rolf Kaiser (ORCID: https://orcid.org/0000-0002-2640-2548)
- Nico Pfeifer (ORCID: https://orcid.org/0000-0002-4647-8566)
- Marta Pingarilho (ORCID: https://orcid.org/0000-0002-7928-3087)
Institutions
- University of Siena (IT)
- Karolinska University Hospital (SE)
- University of Cologne (DE)
- Rega Institute for Medical Research (BE)
- Karolinska Institutet (SE)
- Escola Superior de Saúde Egas Moniz (PT)
- Hospital de Egas Moniz (PT)
- Centro Hospitalar de Lisboa Ocidental (PT)
- University Hospital Cologne (DE)
- Institute of Virology of the Slovak Academy of Sciences (SK)
- University of Tübingen (DE)
- KU Leuven (BE)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1093/bioadv/vbaf099
- Citations
- 1
- Primary Topic
- HIV/AIDS drug development and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.39
Funders
- Deutsches Zentrum für Infektionsforschung
- ViiV Healthcare