Date on Master's Thesis/Doctoral Dissertation
Bioinformatics and Biostatistics
Committee Co-Chair (if applicable)
bayesian; protein phosphorylation; causal inference; ordinal outcome; path analysis; T2DM
This dissertation contains three different projects in proteomics and causal inferences. In the first project, I apply a Bayesian hierarchical model to assess the stability of phosphorylated proteins under short-time cold ischemia. This study provides inference on the stability of these phosphorylated proteins, which is valuable when using these proteins as biomarkers for a disease. in the second project, I perform a comparative study of different confounding-adjusted to estimate the treatment effect when the outcome variable is ordinal using observational data. The adjusted U-statistics method is compared with other methods such as ordinal logistic regression, propensity score based stratification and matching. In the third project, I perform a causal analysis of the combination of dietary information and physical activity in type 2 diabetes across different ethnic groups: White, African American and Mexican American. Such information may contribute to a better understanding of type 2 diabetes variation between ethnic groups, and a better understanding of type 2 diabetes among different ethnic groups and between female and male.
Wu, You, "Bayesian approach on short time-course data of protein phosphorylation, casual inference for ordinal outcome and causal analysis of dietary and physical activity in T2DM using NHANES data." (2017). Electronic Theses and Dissertations. Paper 2751.