Machine Learning for Prediction of HIV Drug Resistance: A Review
Machine Learning for Prediction of HIV Drug Resistance: A Review
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DOI：
10.2174/1574893610666151008011731
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发表时间：
2015-01-01
影响因子：
4
通讯作者：
Bonet, Isis
中科院分区：
文献类型：
--
作者：
Bonet, Isis
几种抗逆转录病毒药物已被批准用于艾滋病毒感染者。尽管科学界做出了努力，但尚未开发出杀死病毒的有效药物。许多计算算法已被用于寻找与耐药性相关的突变以及预测艾滋病毒耐药性。本文概述了用于预测 HIV 耐药性的机器学习技术。将通过以下特征来审查所做的不同类型的研究：问题的不同表示、ARV、降维方法以及所使用的机器学习算法。
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.