Yue (Jason) Zhao Successfully Defends His Thesis

Congratulations to Yue (Jason) Zhao on the successful defense of his thesis, "Data Mining of Host Transcriptome and Microbiome in Pulmonary Disease." Great job Jason!


To learn more about Jason's thesis, read his abstract below:


ABSTRACT

Pulmonary disease is one of the most common and serious medical conditions in the world, and the correct prediction of pulmonary disease such as tuberculosis (TB) and lung cancer can greatly decrease the number of pulmonary disease related deaths. In this thesis, I studied the transcriptome and microbiome difference between pulmonary disease patients and healthy controls, developed and applied several pipelines incorporating bioinformatics methods, statistics and machine learning models to identify patterns in human transcriptome as well as microbiome data for pulmonary disease prediction. Specifically, I evaluated the performance of existing TB disease and TB progression biomarkers, created a bulk RNA-seq gene-expression based biomarker selection pipeline, and identified a 29-gene signature that can correctly predicts TB progression before the TB diagnosis. Next, I developed Animalcules, an R package for microbiome data analysis such as diversity comparison and differential abundance analysis. Finally, I validated the usage of Animalcules by analyzing the nasal microbiome difference between lung cancer patients and control, as well as between current and ex-smoker.



Major Professor: W. Evan Johnson


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