Machine Learning for Prediction of HIV Drug Resistance: A Review

Author(s): Isis Bonet.

Journal Name: Current Bioinformatics

Volume 10 , Issue 5 , 2015

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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.

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

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Article Details

VOLUME: 10
ISSUE: 5
Year: 2015
Page: [579 - 585]
Pages: 7
DOI: 10.2174/1574893610666151008011731
Price: $65

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