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Integrative Statistical Methods for Human Biology, From Biobanks to Perturbation Atlases
Integrative Statistical Methods for Human Biology, From Biobanks to Perturbation Atlases
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103017
- ISBN
- 9798280714939
- DDC
- 574
- 저자명
- Nadig, Ajay.
- 서명/저자
- Integrative Statistical Methods for Human Biology, From Biobanks to Perturbation Atlases
- 발행사항
- [Sl] : Harvard University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 200 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisor: Walsh, Christopher.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2025.
- 초록/해제
- 요약Since the human genome project, many new types of rich biological data have empowered new insight into basic biological science and human disease. Among these are genetic association studies, which characterize many genetic variants in large numbers of individuals, and perturbation atlases, which profile how genetic perturbations shape the expression of thousands of transcripts. However, statistical methods for answering basic questions about these data (How much signal is in each experiment? What is the relationship between experiments? How many discoveries will we make at massive sample size?) lag behind. This thesis presents a suite of novel statistical approaches for the analysis of rich biological data. Our analyses clarify several integrative questions about human biology, ranging from the contribution of rare genetic variation to common diseases, to the consistency of gene perturbation effects across cell types, among others. Looking forward, these methods contribute to the creation of a harmonized analysis toolbox to facilitate replicable characterization and comparison of high-throughput biological experiments.
- 일반주제명
- Bioinformatics
- 일반주제명
- Molecular biology
- 일반주제명
- Genetics
- 키워드
- Biobanks
- 키워드
- Human biology
- 기타저자
- Harvard University Biomedical Informatics
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798280714939
■035 ▼a(MiAaPQ)AAI31843920
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a574
■1001 ▼aNadig, Ajay.▼0(orcid)0000-0001-9634-2141
■24510▼aIntegrative Statistical Methods for Human Biology, From Biobanks to Perturbation Atlases
■260 ▼a[Sl]▼bHarvard University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a200 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisor: Walsh, Christopher.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2025.
■520 ▼aSince the human genome project, many new types of rich biological data have empowered new insight into basic biological science and human disease. Among these are genetic association studies, which characterize many genetic variants in large numbers of individuals, and perturbation atlases, which profile how genetic perturbations shape the expression of thousands of transcripts. However, statistical methods for answering basic questions about these data (How much signal is in each experiment? What is the relationship between experiments? How many discoveries will we make at massive sample size?) lag behind. This thesis presents a suite of novel statistical approaches for the analysis of rich biological data. Our analyses clarify several integrative questions about human biology, ranging from the contribution of rare genetic variation to common diseases, to the consistency of gene perturbation effects across cell types, among others. Looking forward, these methods contribute to the creation of a harmonized analysis toolbox to facilitate replicable characterization and comparison of high-throughput biological experiments.
■590 ▼aSchool code: 0084.
■650 4▼aBioinformatics
■650 4▼aMolecular biology
■650 4▼aGenetics
■653 ▼aBiobanks
■653 ▼aPerturbation atlases
■653 ▼aHuman biology
■690 ▼a0715
■690 ▼a0369
■690 ▼a0307
■71020▼aHarvard University▼bBiomedical Informatics.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17356689▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
