HIV-V3Augur: A Novel Machine Learning Model for Predicting HIV-1 Tropism in Sub-Subtype A6 and CRF63_02A6, Predominant Variants in Russia and Countries of the Former Soviet Union.
- DOI
- 10.3390/v18070703
- Published
- 2026 Jun 25
- Container
- Viruses
- Publisher
- Not recorded
- Open access
- yes
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uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3390/v18070703,
title = {HIV-V3Augur: A Novel Machine Learning Model for Predicting HIV-1 Tropism in Sub-Subtype A6 and CRF63\_02A6, Predominant Variants in Russia and Countries of the Former Soviet Union.},
author = {Elfimov K and Gotfrid L and Nokhova A and Gashnikova M and Ekushov V and Halikov M and Osipova I and Baboshko D and Murzin A and Kondeikin I and Kiryakina A and Totmenin A and Agaphonov A and Gashnikova N},
year = {2026},
journal = {Viruses},
doi = {10.3390/v18070703},
url = {https://doi.org/10.3390/v18070703}
}RIS
TY - JOUR TI - HIV-V3Augur: A Novel Machine Learning Model for Predicting HIV-1 Tropism in Sub-Subtype A6 and CRF63_02A6, Predominant Variants in Russia and Countries of the Former Soviet Union. AU - Elfimov K AU - Gotfrid L AU - Nokhova A AU - Gashnikova M AU - Ekushov V AU - Halikov M AU - Osipova I AU - Baboshko D AU - Murzin A AU - Kondeikin I AU - Kiryakina A AU - Totmenin A AU - Agaphonov A AU - Gashnikova N PY - 2026 JO - Viruses DO - 10.3390/v18070703 UR - https://doi.org/10.3390/v18070703 ER -
APA
K, E., L, G., A, N., M, G., V, E., M, H., I, O., D, B., A, M., I, K., A, K., A, T., A, A., & N, G. (2026). HIV-V3Augur: A Novel Machine Learning Model for Predicting HIV-1 Tropism in Sub-Subtype A6 and CRF63_02A6, Predominant Variants in Russia and Countries of the Former Soviet Union.. Viruses. https://doi.org/10.3390/v18070703
Source records
- pubmed · retrieved 2026-09-25T05:18:17.839Z
- europe-pmc · retrieved 2026-09-25T05:18:17.872Z
- doaj · retrieved 2026-09-25T05:18:17.844Z