基本信息
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Career Trajectory
Bio
My Research
KEYWORDS
Biostatistics, Metagenomics/Microbiomics Data Analysis, Statistical Genomic Methodology, Survey methodology, Study design
SUMMARY
My central research focus is to develop and apply innovative statistical methods to solve challenging data analysis problems in three biomedical research areas: 1) high-throughput metagenomics/microbiome/genetics data analysis, 2) complex survey methodology, and 3) biomedical collaborative research.
I am the director of Metagenomic/Microbiomic Data Analysis Group in Department of Population health. With NIH’s support, my research group has been focused on developing novel statistical methods in analyzing metagenomics and microbiome data, including microbiome association test, longitudinal microbiome data analysis, and microbiome causal/mediation modeling. We work closely with various NYULMC research labs to ensure that the latest statistical methods are incorporated for optimal experimental design and downstream data analysis. We develop best practice data analysis pipelines for a variety of experimental designs that integrate proprietary software from the existing microbiome data analysis platform and the best Open Source tools, as well as software developed within our group.
KEYWORDS
Biostatistics, Metagenomics/Microbiomics Data Analysis, Statistical Genomic Methodology, Survey methodology, Study design
SUMMARY
My central research focus is to develop and apply innovative statistical methods to solve challenging data analysis problems in three biomedical research areas: 1) high-throughput metagenomics/microbiome/genetics data analysis, 2) complex survey methodology, and 3) biomedical collaborative research.
I am the director of Metagenomic/Microbiomic Data Analysis Group in Department of Population health. With NIH’s support, my research group has been focused on developing novel statistical methods in analyzing metagenomics and microbiome data, including microbiome association test, longitudinal microbiome data analysis, and microbiome causal/mediation modeling. We work closely with various NYULMC research labs to ensure that the latest statistical methods are incorporated for optimal experimental design and downstream data analysis. We develop best practice data analysis pipelines for a variety of experimental designs that integrate proprietary software from the existing microbiome data analysis platform and the best Open Source tools, as well as software developed within our group.
Research Interests
Papers共 375 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Science (New York, NY)no. 6708 (2024): eadk5901-eadk5901
Nature Communicationsno. 1 (2024)
Trialsno. 1 (2024): 1-14
bioRxiv : the preprint server for biology (2024)
Sub-cellular biochemistry (2024): 383-408
Lu Hu,Yun Shi,Judith Wylie-Rosett,Mary Ann Sevick,Xinyi Xu,Ricki Lieu,Chan Wang,Huilin Li, Han Bao,Yulin Jiang, Ziqiang Zhu,Ming-Chin Yeh,
PLOS ONEno. 3 (2024): e0299799-e0299799
JOURNAL OF MOLECULAR STRUCTURE (2024): 137336
Journal of Biological Chemistrypp.107387, (2024)
Nature Structural & Molecular Biologypp.1-12, (2024)
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Author Statistics
#Papers: 360
#Citation: 21135
H-Index: 70
G-Index: 141
Sociability: 7
Diversity: 4
Activity: 228
Co-Author
Co-Institution
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