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Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Meta-analysis is a widely used tool to combine research findings from multiple studies in many disciplines. In this thesis we develop novel methods to deal with two critical issues in systematic reviews and meta-analyses, such as...
Bayesian additive regression trees(BART) provides flexible approach to fitting a variety of regression models while avoiding strong parametric assumptions. The sum-of-trees model is embedded in a Bayesian inferential framework to support...
Over the past 30 years, magnetic resonance imaging has become a ubiquitous tool for accurately visualizing the change and development of the brain subcortical structures (e.g., hippocampus) across time and group. Although subcortical...
Protecting individuals' private information while still allowing modelers to draw inferences from confidential data sets is a concern of many data producers. Differential privacy is a framework that enables statistical analyses while...
Reusability is part of the FAIR data principle, which aims to make data Findable, Accessible, Interoperable, and Reusable. One of the current efforts to increase the reusability of public genomics data has been to focus on the inclusion...
Investigating Significant Mutations of US SARS-CoV-2 RNA Sequences Using Stratified Spaces, and Genetic Connection to Drug-Induced Liver Injury (DILI) through Statistical Learning Methods
The first half of this dissertation aims to give a motivation for working with metric tree data. We give a brief introduction and application of data analysis on stratified spaces with special emphasis on phylogenetic tree data analysis....
Ideas from the algebraic topology of studying object data are used to introduce a framework for using persistence landscapes to vectorized objects. These methods are applied to analyze data from The Cancer Imaging Archive (TCIA), using a...
Deep neural networks have drawn much attention due to their success in various vision tasks. Incremntal Leaning is a paradigm where instances from new object classes are added sequentially. The traditional training scheme causes a...
PPCA-Xnorm: A Probabilistic Principal Component Analysis (PPCA) Based Approach to Performing Cross Platform Normalization on Two or More Gene Expression Platforms
We introduce PPCA-Xnorm, a method we developed to perform cross platform normalization of gene expression values across two or more gene platforms. PPCA-Xnorm is based on a Probabilistic Principal Component Analysis (PPCA) model. The...
In the classical literature of Statistics, a large amount of methods have been addressed for data analysis on Euclidean space. Over the past few decades, however, a growing interest has been devoted to non-Euclidean data analysis. In...
We consider change-point detection and estimation in two different settings. The objective is to halt a process when the process generating observations deviates from a specified in control standard, in which case the process is referred...
Project 1: ProDCoNN: Protein Design using a Convolutional Neural Network. Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with...
In the past decade, there has been an exponential increase in the volume of biomedical literature, creating a wealth of life sciences knowledge in need of automated curation. This automated extraction process is termed Information...
Replicability is the cornerstone of scientific research. In this dissertation, we study replicability analysis of multiple studies from high throughput experiments, where tens of thousands of features are examined simultaneously. In the...
Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
