Browsing by Author "Zhang, David Y"

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    Rational Design and Optimization of Nucleic Acid Hybridization
    (2018-05-30) Fang, John; Zhang, David Y
    Nucleic acid interaction plays a crucial part in many common biological mechanisms, ranging from protein synthesis to cell replication. Hydrogen-bonding between complementary nucleic acid base pairs, also known as hybridization, is one of the most prominent interactions; the unique chemistry of these nucleic acid bases allow for precise yet reversible pairing. By characterizing the thermodynamic and kinetic mechanisms behind nucleic acid hybridization, it is possible to predict and quantitate the progress of nucleic acid hybridization at chemical equilibrium, or even before reaching equilibrium. In this thesis, I will explain my understanding, characterization, and prediction of nucleic acid hybridization systems, as well as how this knowledge can improve the design of DNA-based molecular diagnostics. The first two projects revolve around the double-stranded probe known as the “toehold” probe and how it can be modified to span a dynamic range of multiple orders of magnitude without the use of enzymes; I also explain my attempt to construct a probe system that could theoretically discriminate targets with different numbers of mismatches. The last two projects explore the previously uncharted territory of DNA hybridization kinetics, building predictive machine learning algorithms based of experimental hybridization kinetic data, and scaling this towards predicting kinetics in highly multiplexed settings.
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    Simple, Multiplexed, and Ultraspecific Nucleic Acid-based Diagnostic Technologies
    (2017-06-15) Wu, Ruojia; Zhang, David Y
    The economical and high-throughput detection and quantitation of disease-relevant nucleic acid sequences is a key goal in the road to widespread adoption of precision medicine, wherein optimal individualized treatment is provided to each patient based on his or her unique genetic and disease profile. Current widely used technology platforms such as microarray, NGS, and PCR are either expensive and time-consuming, or difficult to scale up to multiplexed assays. Additionally, highly specific and sensitive detection of small nucleotide variants is still challenging using conventional methods. During my PhD, I have developed several novel molecular approaches to improve the specificity and / or multiplexibility of existing technology platforms, and further validated them using biological and clinical samples. The philosophy behind these works is to pursue reliable in silico assay design and thus less empirical optimization, to develop methods that are generalizable to any target sequence in the genome, and to make the experimental procedures simple, cheap, and fast.