Sandrine Dudoit

Sandrine Dudoit, PhD
Professor, Division of Biostatistics, School of Public Health, and Department of Statistics
Chair and Head Graduate Advisor, Graduate Group in Biostatistics
University of California, Berkeley

101 Haviland Hall, #7358
Berkeley, CA 94720-7358
Fax: (510) 643-5163
E-mail: sandrine@stat.berkeley.edu










N.B. Prospective graduate students. Please take the time to read carefully the information on the program website before contacting us. You will find answers to most of your questions regarding application procedures, admission criteria, degree requirements, and financial support on this website. If you still have questions, please contact biostat@berkeley.edu regarding administrative matters or me for academic matters.



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NEWS

Postdoctoral position in adductomics and metabolomics [Announcement]

PB HLTH 295 -- Statistics and Genomics Seminar

PB HLTH C240D/STAT C245D -- Biostatistical Methods: Computational Statistics with Applications in Biology and Medicine

Publications

Software

Presentations


Research and Teaching Activities

My research and teaching activities concern the development and application of statistical methods and software for the analysis of biomedical and genomic data.

Statistical methodology. My methodological research interests regard high-dimensional inference and include exploratory data analysis (EDA), visualization, loss-based estimation with cross-validation (e.g., density estimation, regression, model selection), and multiple hypothesis testing.

Applications to biomedical and genomic research. Much of my 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., RNA-Seq for transcriptome analysis and genome annotation and ChIP-Seq for DNA-protein interaction profiling (e.g., transcription factor binding). My contributions include: exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery, prediction, integration of biological annotation metadata (e.g., Gene Ontology (GO) annotation).

Statistical computing. I am also interested in statistical computing and, in particular, reproducible research. I am 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.


Curriculum Vitae and Biography

Curriculum Vitae: [PDF]

Biography: [PDF] [Word]


Affiliations



Employment Opportunities