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     High mutation rate in HIV, and RNA viruses in general, often leads to drug resistance. This discussion will focus on computational approaches on estimating these mutational pathways, and their usefulness in designing drug therapy.

    Required Reading:

    1.  Estimating HIV Evolutionary Pathways and the Genetic Barrier to Drug Resistance. Link

    2.  A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance. Link

    3.  Bioinformatics-assisted anti-HIV therapy. Link

    Optional Reading:

    1. A very short note on optimal HIV mutation rate:

     HIV Mutation Rate. Link

    2.  Detailed description of mutagenic trees model mentioned in "Estimating HIV Evolutionary Pathways and the Genetic Barrier to Drug Resistance" paper:

    Learning Multiple Evolutionary Pathways from Cross-sectional Data. Link

    3. A Markov Model extension of the mutagenic tree model: 

    A mutagenic tree hidden Markov model for longitudinal clonal HIV sequence data. Link 

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