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Models and Inference for Microbiome Data
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Models and Inference for Microbiome Data. |
| 개인저자 | Tang, Yunfan. |
| 단체저자명 | The University of Chicago. Statistics. |
| 발행사항 | [S.l.]: The University of Chicago., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 103 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
| ISBN | 9780438088436 |
| 학위논문주기 | Thesis (Ph.D.)--The University of Chicago, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Dan L. Nicolae. |
| 요약 | Microbiome refers to the full collection of all microorganisms in a community. Recent advances in sequencing technologies have allowed scientists to quantify the microbiome compositions at an unprecedented resolution. However, high-throughput se |
| 일반주제명 | Statistics. Biostatistics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
