Skip to main content

ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Status
  • Public
Date Range
2010 2019


DNA and RNA are generally regarded as one of the central molecules in molecular biology. Recent advancements in the field of DNA/RNA nanotechnology witnessed the success of usage of DNA/RNA as programmable molecules to construct nano-objects with predefined shapes and dynamic molecular machines for various functions. From the perspective of structural design with nucleic acid, there are basically two types of assembly method, DNA tile based assembly and DNA origami based assembly, used to construct infinite-sized crystal structures and finite-sized molecular structures. The assembled structure can be used for arrangement of other molecules or nanoparticles with the resolution of nanometers …

Contributors
Hong, Fan, Yan, Hao, Liu, Yan, et al.
Created Date
2019

The highly predictable structural and thermodynamic behavior of deoxynucleic acid (DNA) and ribonucleic acid (RNA) have made them versatile tools for creating artificial nanostructures over broad range. Moreover, DNA and RNA are able to interact with biological ligand as either synthetic aptamers or natural components, conferring direct biological functions to the nucleic acid devices. The applications of nucleic acids greatly relies on the bio-reactivity and specificity when applied to highly complexed biological systems. This dissertation aims to 1) develop new strategy to identify high affinity nucleic acid aptamers against biological ligand; and 2) explore highly orthogonal RNA riboregulators in vivo …

Contributors
Zhou, Yu, Yan, Hao, Green, Alexander, et al.
Created Date
2019

Aging-related damage and failure in structures, such as fatigue cracking, corrosion, and delamination, are critical for structural integrity. Most engineering structures have embedded defects such as voids, cracks, inclusions from manufacturing. The properties and locations of embedded defects are generally unknown and hard to detect in complex engineering structures. Therefore, early detection of damage is beneficial for prognosis and risk management of aging infrastructure system. Non-destructive testing (NDT) and structural health monitoring (SHM) are widely used for this purpose. Different types of NDT techniques have been proposed for the damage detection, such as optical image, ultrasound wave, thermography, eddy current, …

Contributors
Chang, Qinan, Liu, Yongming, Mignolet, Marc, et al.
Created Date
2019

Image-based process monitoring has recently attracted increasing attention due to the advancement of the sensing technologies. However, existing process monitoring methods fail to fully utilize the spatial information of images due to their complex characteristics including the high dimensionality and complex spatial structures. Recent advancement of the unsupervised deep models such as a generative adversarial network (GAN) and generative adversarial autoencoder (AAE) has enabled to learn the complex spatial structures automatically. Inspired by this advancement, we propose an anomaly detection framework based on the AAE for unsupervised anomaly detection for images. AAE combines the power of GAN with the variational …

Contributors
YEH, HUAI-MING, Yan, Hao, Pan, Rong, et al.
Created Date
2019

Though DNA nanostructures (DNs) have become interesting subjects of drug delivery, in vivo imaging and biosensor research, however, for real biological applications, they should be ‘long circulating’ in blood. One of the crucial requirements for DN stability is high salt concentration (like ~5–20 mM Mg2+) that is unavailable in a cell culture medium or in blood. Hence DNs denature promptly when injected into living systems. Another important factor is the presence of nucleases that cause fast degradation of unprotected DNs. The third factor is ‘opsonization’ which is the immune process by which phagocytes target foreign particles introduced into the bloodstream. …

Contributors
Banerjee, Saswata, Yan, Hao, Angell, Austen, et al.
Created Date
2018

Extracellular vesicles (EVs) represent a heterogeneous population of small vesicles, consisting of a phospholipidic bilayer surrounding a soluble interior cargo. These vesicles play an important role in cellular communication by virtue of their protein, RNA, and lipid content, which can be transferred among cells. Peripheral blood is a rich source of circulating EVs. An analysis of EVs in peripheral blood could provide access to unparalleled amounts of biomarkers of great diagnostic, prognostic as well as therapeutic value. In the current study, a plasma EV enrichment method based on pluronic co-polymer was first established and characterized. Plasma EVs from breast cancer …

Contributors
Zhong, Zhenyu, Spetzler, David, Yan, Hao, et al.
Created Date
2018

Modern, advanced statistical tools from data mining and machine learning have become commonplace in molecular biology in large part because of the “big data” demands of various kinds of “-omics” (e.g., genomics, transcriptomics, metabolomics, etc.). However, in other fields of biology where empirical data sets are conventionally smaller, more traditional statistical methods of inference are still very effective and widely used. Nevertheless, with the decrease in cost of high-performance computing, these fields are starting to employ simulation models to generate insights into questions that have been elusive in the laboratory and field. Although these computational models allow for exquisite control …

Contributors
Seto, Christian, Pavlic, Theodore, Li, Jing, et al.
Created Date
2018

Transfer learning is a sub-field of statistical modeling and machine learning. It refers to methods that integrate the knowledge of other domains (called source domains) and the data of the target domain in a mathematically rigorous and intelligent way, to develop a better model for the target domain than a model using the data of the target domain alone. While transfer learning is a promising approach in various application domains, my dissertation research focuses on the particular application in health care, including telemonitoring of Parkinson’s Disease (PD) and radiomics for glioblastoma. The first topic is a Mixed Effects Transfer Learning …

Contributors
Yoon, Hyunsoo, Li, Jing, Wu, Teresa, et al.
Created Date
2018

There are many biological questions that require single-cell analysis of gene sequences, including analysis of clonally distributed dimeric immunoreceptors on lymphocytes (T cells and B cells) and/or the accumulation of driver/accessory mutations in polyclonal tumors. Lysis of bulk cell populations results in mixing of gene sequences, making it impossible to know which pairs of gene sequences originated from any particular cell and obfuscating analysis of rare sequences within large populations. Although current single-cell sorting technologies can be used to address some of these questions, such approaches are expensive, require specialized equipment, and lack the necessary high-throughput capacity for comprehensive analysis. …

Contributors
Schoettle, Louis Noble, Blattman, Joseph N, Yan, Hao, et al.
Created Date
2017

Nature is a master at organizing biomolecules in all intracellular processes, and researchers have conducted extensive research to understand the way enzymes interact with each other through spatial and orientation positioning, substrate channeling, compartmentalization, and more. DNA nanostructures of high programmability and complexity provide excellent scaffolds to arrange multiple molecular/macromolecular components at nanometer scale to construct interactive biomolecular complexes and networks. Due to the sequence specificity at different positions of the DNA origami nanostructures, spatially addressable molecular pegboard with a resolution of several nm (less than 10 nm) can be achieved. So far, DNA nanostructures can be used to build …

Contributors
Yang, Yuhe Renee, Yan, Hao, Liu, Yan, et al.
Created Date
2016