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Sandrine Dudoit is Professor and Chair of the Department of Statistics and Professor in the Division of Biostatistics, School of Public, at the University of California, Berkeley. Professor Dudoit's methodological research interests regard high-dimensional inference and include exploratory data analysis (EDA),visualization, loss-based estimation with cross-validation (e.g., density estimation, classification, regression, model selection), and multiple hypothesis testing. Much of her methodological work is motivated by statistical inference questions arising in biological research and, in particular, the design and analysis of high-throughput microarray and sequencing gene expression experiments,e.g., single-cell transcriptome sequencing (RNA-Seq) for discovering novel cell types and for the study of stem cell differentiation. Her contributions include:exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery, prediction, inference of cell lineages,integration of biological annotation metadata (e.g., Gene Ontology (GO)annotation). She is also interested in statistical computing and, in particular,reproducible research. She is a founding core developer of the Bioconductor Project (http://www.bioconductor.org), an open-source and open-development software project for the analysis of biomedical and genomic data.
研究兴趣
论文共 182 篇作者统计合作学者相似作者
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Nature Communicationsno. 1 (2024): 1-16
arXiv (Cornell University) (2023)
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Koen Van den Berge,Hsin-Jung Chou, Divya Kunda,Davide Risso,Kelly Street,Elizabeth Purdom,Sandrine Dudoit,John Ngai, Whitney Heavner
bioRxiv : the preprint server for biology (2023)
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Cell reports methodsno. 11 (2022): 100321
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