자료유형 | 학위논문 |
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서명/저자사항 | Accurate, Automated, and Scalable Identification of RNA Structure Motifs in Structurome Profiling Data. |
개인저자 | Radecki, Pierce. |
단체저자명 | University of California, Davis. Biomedical Engineering. |
발행사항 | [S.l.]: University of California, Davis., 2021. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2021. |
형태사항 | 179 p. |
기본자료 저록 | Dissertations Abstracts International 83-02B. Dissertation Abstract International |
ISBN | 9798538101115 |
학위논문주기 | Thesis (Ph.D.)--University of California, Davis, 2021. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Advisor: Aviran, Sharon. |
이용제한사항 | This item must not be sold to any third party vendors. |
일반주제명 | Biomedical engineering. Algorithms. Ribonucleic acid--RNA. Artificial intelligence. Genetics. Virology. Datasets. Severe acute respiratory syndrome coronavirus 2. Nuclear magnetic resonance--NMR. Binding sites. Feature selection. Genomes. E coli. Friendship. Proteins. Human immunodeficiency virus--HIV. Biopolymers. Experiments. Immune system. Deoxyribonucleic acid--DNA. Methods. Roles. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |