Rational Design and Optimization of Nucleic Acid Hybridization
| dc.contributor.advisor | Zhang, David Y | en_US |
| dc.creator | Fang, John | en_US |
| dc.date.accessioned | 2019-05-17T15:43:43Z | en_US |
| dc.date.available | 2019-05-17T15:43:43Z | en_US |
| dc.date.created | 2018-08 | en_US |
| dc.date.issued | 2018-05-30 | en_US |
| dc.date.submitted | August 2018 | en_US |
| dc.date.updated | 2019-05-17T15:43:43Z | en_US |
| dc.description.abstract | 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. | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.citation | Fang, John. "Rational Design and Optimization of Nucleic Acid Hybridization." (2018) Diss., Rice University. <a href="https://hdl.handle.net/1911/105805">https://hdl.handle.net/1911/105805</a>. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/105805 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | en_US |
| dc.subject | Biophysics | en_US |
| dc.subject | Machine Learning | en_US |
| dc.subject | DNA | en_US |
| dc.subject | Thermodynamics | en_US |
| dc.subject | Diagnostics | en_US |
| dc.title | Rational Design and Optimization of Nucleic Acid Hybridization | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Bioengineering | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy | en_US |
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