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Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks
BACKGROUND: Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of prescribing sub-optimal drug regimens leading to p...
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| Publié dans: | BMC Bioinformatics |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
BioMed Central
2017
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5558779/ https://ncbi.nlm.nih.gov/pubmed/28810826 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-017-1782-x |
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