Physical Sciences and Mathematics Commons^™

Application Of Machine Learning To Mapping And Simulating Gene Regulatory Networks, Hien-Haw Liow

Arts & Sciences Electronic Theses and Dissertations

This dissertation explores, proposes, and examines methods of applying modernmachine learning and Bayesian statistics in the quantitative and qualitative modeling of gene regulatory networks using high-throughput gene expression data. A semi-parametric Bayesian model based on random forest is developed to infer quantitative aspects of gene regulation relations; a parametric model is developed to predict geneexpression levels solely from genotype information. Simulation of network behavior is shown to complement regression analysis greatly in capturing the dynamics of gene regulatory networks. Finally, as an application and extension of novel approaches in gene expression analysis, new methods of discovering topological structure of gene …

Comparison Of Conventional And Bayesian Analysis For The Ultrasonic Characterization Of Cancellous Bone, Amber Groopman

Arts & Sciences Electronic Theses and Dissertations

This dissertation investigates the physics underlying the propagation of ultrasonic waves in cancellous bone. Although quantitative ultrasound has the potential to evaluate bone quality even better than the current gold standard X-ray based modality, its clinical utility has been hampered by the incomplete understanding of the mechanisms governing the interaction between ultrasound and bone. Therefore, studies that extend the understanding of the fundamental physics of the relationship between ultrasound and trabecular bone tissue may result in improved clinical capabilities.

Ultrasonic measurements were carried out on excised human calcaneal specimens in order to study the effects of overlapping fast and slow …