Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks

Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks

Abstract 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 lead...

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Bibliographic Details
Main Authors: Olivier Sheik Amamuddy, Nigel T. Bishop, Özlem Tastan Bishop
Format: Article
Language:English
Published: BMC 2017-08-01
Series:BMC Bioinformatics
Subjects:
Artificial neural network
Drug resistance prediction
Subtype-specific training
HIV-1 subtype B
HIV reverse transcriptase
HIV protease
Online Access:http://link.springer.com/article/10.1186/s12859-017-1782-x

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http://link.springer.com/article/10.1186/s12859-017-1782-x

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