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Learning about Sequence-dependent DNA/Single-wall Carbon Nanotube Hybrids
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Learning about Sequence-dependent DNA/Single-wall Carbon Nanotube Hybrids. |
| 개인저자 | Yang, Yoona. |
| 단체저자명 | Lehigh University. Chemical Engineering. |
| 발행사항 | [S.l.]: Lehigh University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 190 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
| ISBN | 9781088374467 |
| 학위논문주기 | Thesis (Ph.D.)--Lehigh University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Jagota, Anand. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Since the single-wall carbon nanotubes (SWCNTs) were discovered in 1993, they have attracted significant interest with their extraordinary electrical and optical properties in addition to their remarkable mechanical strength and thermal conductivity. Single-stranded DNA conjugated SWCNT have shown outstanding functionality in terms of dispersibility and biocompatibility. In addition, some special DNA sequences have presented an ability to recognize specific SWCNT species, called recognition sequences. Ion-exchange chromatography and aqueous two-phase (ATP) separation technique have been widely used for SWCNT separation. However, little is known about the use of ATP as an analytical technique. Furthermore, for bio-applications, DNA/SWCNT hybrids have attracted significant interest due to their high solvatochromic sensitivity to changes in the local environment, which enables their use as sensors. Recognition properties can provide good candidates for molecular detection on the assumption that the recognition DNA/SWCNT hybrids have structurally well-defined DNA wrappings. Thus, there is a growing need for discovery of new recognition sequences. In this thesis, we explore new methods to quantify difference in solvation/binding characteristics using ATP, and a new approach to predicting recognition sequences using Machine Learning techniques. Finally, a new concept for a DNA/SWCNT-based sensing system is demonstrated. |
| 일반주제명 | Chemical engineering. Nanotechnology. Bioinformatics. |
| 언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
