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HIV-1 Sequence Analysis: Approaches and Applications from Transmission Network Inference to Epitope Discovery
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | HIV-1 Sequence Analysis: Approaches and Applications from Transmission Network Inference to Epitope Discovery. |
| 개인저자 | Hepler, Nicolaus Lance. |
| 단체저자명 | University of California, San Diego. Bioinformatics and Systems Biology. |
| 발행사항 | [S.l.]: University of California, San Diego., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 142 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-02B. Dissertation Abstract International |
| ISBN | 9781085575140 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, San Diego, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Advisor: Kosakovsky Pond, Sergei L. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | Recent advances in sequencing technology, especially next-generation sequencing (NGS), have become central to the study of rapidly evolving pathogens such as HIV-1. However, one must contend with the massive amount of data produced by NGS as well as artifacts arising from sample preparation and sequencing. To deal with these complexities, numerous bioinformatics methods have appeared to enable researchers to extract the maximum value from their sequencing data. Unfortunately, the number of methods and the difficulty of benchmarking have limited their reach |
| 일반주제명 | Bioinformatics. Artificial intelligence. Virology. |
| 언어 | 영어 |
| 바로가기 | 
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