Machine Learning for Prediction of HIV Drug Resistance: A Review

Title:Machine Learning for Prediction of HIV Drug Resistance: A Review

Volume: 10 Issue: 5

Author(s): Isis Bonet

Affiliation:

Keywords: HIV prediction, machine learning, feature selection, feature extraction, drug resistance.

Abstract: Several antiretroviral drugs have been approved for use in HIV infected people. Despite efforts made by the scientific community, an effective drug that kills the virus has not been developed yet. A lot of computational algorithms have been used for finding mutations associated with drug resistance as well as for prediction of HIV resistance. This article provides an overview of machine learning techniques used to predict the HIV drug resistance. The different types of studies done will be reviewed through the following characteristics: different representations of the problem, ARVs, methods to reduce dimensionality and algorithms of machine learning used.

Cite this article as:

Bonet Isis, Machine Learning for Prediction of HIV Drug Resistance: A Review, Current Bioinformatics 2015; 10 (5) . https://dx.doi.org/10.2174/1574893610666151008011731