• Teachings

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    Single (Simple) Nucleotide Polymorphisms (SNPs) and Genome-wide Association Studies

    Learning objectives: after the class, students are expected to

    • explain the concepts of SNPs
    • explain potential applications of SNPs, which may include identification, GWAS, predisposition to diseases, personalized medicine
    • understand the concept of haplotypes and Linkage Disequilibrium, able to estimate LD based on given data
    • understand where one can look up information for SNPs and open resources for SNP data
    • explain the concept of GWAS and the medical applications of GWAS
    • understand the standard design of a GWAS stud
    • elaborate the outcomes and impacts of a couple state-of-the-art GWAS studies
    Teaching Materials
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    Predictive Models for Healthcare Analytics

    Learning objectives: after the class, students are expected to

    • define what are predictive models
    • apply appropriate metrics to assess the performance of predictive models
    • explain some basic predictive models, such as logistic regression, decision tree, neural network etc
    • conduct retrospective clinical studies with appropriate predictive models
    • interpret results from predictive models
    • understand the future trend of predictive models