Sandrine Dudoit
Associate
Professor of Biostatistics and Statistics
Chair and Head
Graduate Advisor, Graduate
Group in Biostatistics
Division of
Biostatistics
School of Public Health
University of California, Berkeley
101 Haviland Hall, #7358
Berkeley, CA 94720-7358
Tel: (510) 643-1108
Fax: (510) 643-5163
E-mail: sandrine@stat.berkeley.edu
Photo by Laurent
Dudoit
Selected Works
Website
SPH Webpage
VCRO
Webpage
Curriculum Vitae
NEWS
Multiple Testing
Procedures with Applications to Genomics
(2008).
S. Dudoit and M. J.
van der Laan.
Springer Series in
Statistics.
Order: [Springer]
[Amazon]
ScienceMatters@Berkeley
- Statistical Challenges in Genomics
BIRS
2008 - Emerging Statistical Challenges in Genome and Translational
Research
Banff International Research Station, Banff, Canada, June 01-06,
2008
[Wiki] [Program]
PB
HLTH 292 - Fall 2008 Statistics and Genomics Seminar
Research and
Teaching Activities
I am an Associate Professor in the Division of Biostatistics
and
Department of Statistics at
the University of California,
Berkeley.
My research and teaching activities concern the development and
application of statistical and computational methods to address
problems in biomedical and genomic research.
Specific areas of interest include:
- the design and analysis of high-throughput gene expression
experiments based on next-generation sequencing: transcriptome
analysis, genome annotation;
- the design and analysis of high-throughput gene expression
experiments based on DNA microarrays: cDNA microarrays,
alternative splicing microarrays, ChIP-Chip, metagenomics microarrays;
- nucleotide and protein sequence analysis: identification
of
regulatory motifs in DNA sequences;
- the genetic mapping of complex traits: IBD-based linkage
analysis, linkage disequilibrium analysis, SNP-based association
studies, microarray-based genetic mapping studies of gene expression;
- the analysis of biological annotation metadata: Gene
Ontology (GO) annotation.
My methodological research interests include:
- loss-based estimation with cross-validation: parametric
and
non-parametric density estimation and regression, variable selection;
- multiple hypothesis testing: resampling-based multiple
testing
procedures for controlling generalized Type I error rates, defined as
tail
probabilities and expected values for arbitrary functions of the
numbers of Type I errors and rejected hypotheses (e.g., false discovery
rate).
I am also interested in statistical computing and I am a core
developer
of the Bioconductor
Project, an open-source and open-development software project for
the analysis of biomedical and genomic data.
Affiliations
Graduate Group in
Biostatistics, UC Berkeley
Graduate
Group in Computational and Genomic Biology, UC Berkeley
Graduate
Group in Computational Science and Engineering (CSE), UC Berkeley
Center for Computational Biology
(CCB), UC Berkeley
Center for
Integrative Genomics (CIG), UC Berkeley
California Institute for
Quantitative Biosciences (QB3)
Center for Bioinformatics
and
Molecular Biostatistics (CBMB), UC San Francisco
Bioconductor Project Core
Developer
Biography
I first came to UC Berkeley in
1994 as a PhD student, after earning a
BSc and an MSc in Mathematics from Carleton
University, Ottawa,
Canada.
For my doctoral
thesis, I worked with Terry Speed on
statistical methods for the genetic mapping of complex human traits.
After
graduating from the Department
of Statistics in May 1999, I was a
postdoctoral fellow at the Mathematical
Sciences Research Institute in Berkeley from September 1999 until
June 2000. From July 2000 until June
2001, I was a postdoctoral fellow in Pat Brown's lab in the Department
of Biochemistry at Stanford
University. My work in the lab involved the
development of statistical and computational methods for the design and
analysis of DNA microarray experiments. I joined the Faculty of the UC Berkeley Division of Biostatistics
in July 2001 and Department of
Statistics in November 2006.