Jürgen von Frese
Jürgen von Frese is associate professor for bioinformatics and chemometrics at the The Royal Veterinary & Agricultural University (KVL) in Denmark. He has been involved in all aspects of microarray analysis since 1998. He has worked on algorithm development and has been the responsible biostatistician in numerous microarray studies, collaborating e.g. with Affymetrix and Roche Diagnostics. – He has been involved in the largest international effort to date for bringing microarray based cancer diagnostics into practice, comprising a study with 1200 whole genome chipsets on more than 16 leukemia classes. He is regularly teaching microarray analysis to industry.
Bioinformatics & Chemometrics Dep. of Food Science The Royal Veterinary & Agricultural University Rolighedsvej 30
DK-1958 Frederiksberg C
Denmark
Phone: +45 35 28 32 54
Fax: +45 35 28 32 45
Email: jvf@kvl.dk
www.models.kvl.dk

Ursula Sauer
Ursula Sauer is working in biochip related projects at ARCS since 2001.
Her main expertise is in the field of oligo as well as protein microarrays. She is experienced in all processes involved in development, production, optimization and validation of biochips. Her special interest is data analysis and quality control of both, data and methods.
ARC Seibersdorf research GmbH
Biogenetics - Natural Resources
A-2444 Seibersdorf
Tel. +43-50 550-3527
Fax: +43 50 550-3666
Email: ursula.sauer@arcs.ac.at

Ben Bolstad
Berkeley, California, USA
Email : bmb@bmbolstad.com
http://bmbolstad.com

John D. Storey
DEPARTMENT OF BIOSTATISTICS
DEPARTMENT OF GENOME SCIENCES
UNIVERSITY OF WASHINGTON
http://faculty.washington.edu/jstorey/

Yudi Pawitan
Department of Medical Epidemiology and Biostatistics
Karolinska Institutet
P.O. Box 281
SE-171 77 Stockholm
Sweden
http://www.meb.ki.se/~yudpaw

Krina Zondervan
Research Fellow in Genetic Epidemiology
Wellcome Trust Centre for Human Genetics
Roosevelt Drive Oxford OX3 7BN
Tel +44 (0)1865 287627
Fax +44 (0)1865 287927
Email: krinaz@well.ox.ac.uk

Jaya Satagopan PhD
Department of Epidemiology and Biostatistics
Memorial Sloan-Kettering Cancer Center
307, East 63rd Street
New York, NY 10021
USA
Email: satagopj@mskcc.org
Phone: (646) 735-8122

Richard S. Spielman, Ph.D.
University of Pennsylvania
School of Medicine
464 Clinical Research Building
415 Curie Boulevard
Philadelphia, Pennsylvania 19104-6145

David Edwards
David Edwards is principal scientist at the Biostatistics Department, Novo Nordisk, and honorary professor at the University of Bremen. His research interests include model selection, graphical modelling (he has authored an introductory textbook on the topic), microarray analysis, randomisation inference and clinical trials methodology.
Biostatistics Department
Novo Nordisk A/S
Krogsjhøjvej
DK-2880 Bagsværd
Denmark

David M. Rocke
Division of Biostatistics (Medicine),
Department of Applied Science (Engineering), & Institute for Data Analysis and Visualization University of California, Davis
2343 Academic Surge Building
University of California, Davis
One Shields Avenue
Davis, CA 95616-8553
Phone: 530.752.0510
Fax: 530.752.8894
Email: dmrocke@ucdavis.edu
www.idav.ucdavis.edu/~dmrocke

Marina Vannucci
Marina Vannucci is Professor of Statistics at Texas A&M University. She
got a Ph.D. in Statistics in 1996, from the University of Florence, Italy.
She then held a postoctoral position at the University of Kent at Canterbury, UK. She joined Texas A&M University in 1998. Her research has focused on the theory and practice of Bayesian variable selection
techniques and on the development of wavelet-based statistical models and their applications. Her work has been often motivated by real problems that needed to be addressed with suitable statistical methods. DNA microarray data are characterized by many variables (gene expressions) and relatively few samples. These studies often aim either at predicting different types of tissues or diseases or at the discovery of unknown subtypes (particularly in cancer studies). In addition, it is important that the identified molecular classes are defined on a small number of genes that can serve as biomarkers for improved diagnosis and therapeutic intervention. Professor Vannucci's work has focused on the development of Bayesian methods that offer a coherent framework in which variable selection and classification or clustering of the samples are performed simultaneously. Her work has been applied to microarrays and proteomic data. She has also worked on models that combine DNA microarrays with genome sequences to identify binding sites for regulatory factors.
Department of Statistics
439 Blocker Building
Texas A&M University
3143 TAMU
College Station TX 77843-3143
USA
Phone: +1-979-845-3164
Fax: +1-979-845-3144
Email : mvannucci@stat.tamu.edu
http://stat.tamu.edu/~mvannucci/

John Whittaker
John took a BSc in Mathematics (1988) and a PhD in Statistics (1992) at the University of Sheffield. After a year lecturing Statistics at the University of Newcastle, he did postdoctoral work on QTL mapping in inbred line crosses at the University of Reading and the Roslin Institute, Edinburgh. Subsequent work in genetic epidemiology, first at the University of Reading and then at Imperial College London, has concentrated in methodology for genetic association studies, particularly family based studies and fine scale mapping in population samples. Other interests are in the analysis of gene expression data, particularly genetical genomics, proteomics and the analysis of whole genome association studies. Much of this work is based on Bayesian models implemented via MCMC. John moved to a Chair of Genetic Epidemiology and Statistics at the London School of Hygiene and Topical Medicine in April 2005.
Department of Epidemiology and Population Health
London School of Hygiene & Tropical Medicine
Keppel Street
London WC1E 7HT
Phone: +44 (0)20 7927 2025
Fax : +44 (0)20 7580 6897
Email : john.whittaker@lshtm.ac.uk

Arief Gusnanto
MRC Biostatistics Unit
Institute of Public Health
Forvie Site, Robinson Way
Cambridge CB2 2SR
United Kingdom
Ph. +44 (1223) 767408
Fax +44 (1223) 330388
Email : Arief.Gusnanto@mrc-bsu.cam.ac.uk
http://www.mrc-bsu.cam.ac.uk/personal/arief

Brian D M Tom
Brian Tom is a statistician at the Medical Research Council Biostatistics Unit since December 2001. His research areas are quite varied, ranging from epidemiology to biostatistics and bioinformatics.He is currently involved in projects on chronic diseases such as hepatitis C virus, psoriatic arthritis, mental illnesses and cardiovascular disease. His interests in the area of bioinformatics, have been mainly in the area of microarrays (analysis, quality determination, and data fusion), although he is presently involved on projects to do with pseudo-genes and transcription binding site prediction. He is part of the statistical team involved in the EU funded Bloodomics consortium whose aim is to investigate the role of platelets and other blood cells in heart disease.
Medical Research Council Biostatistics Unit Institute of Public Health University Forvie Site Robinson Way
Cambridge CB2 2SR
United Kingdom
Tel no: +44 1223 330 395
Email : brian.tom@mrc-bsu.cam.ac.uk

Luisa Bernardinelli
MRC Biostatistics Unit
Institute of Public Health
Forvie Site, Robinson Way
Cambridge CB2 2SR
United Kingdom
Ph. +44 (1223) 330300
Fax +44 (1223) 330388
Dipartimento di Scienze Sanitarie Applicate
Università di Pavia
http://www.unipv.it/webdssap/upload/laboratori/statgen/

Carlo Berzuini
MRC Biostatistics Unit
Institute of Public Health
Forvie Site, Robinson Way
Cambridge CB2 2SR
United Kingdom
Ph. +44 (1223) 330300
Fax +44 (1223) 330388
Dipartimento di Informatica e Sistemistica
Università di Pavia
Via Ferrata1, 27100 Pavia

Chris Holmes
Department of Statistics
University of Oxford
Oxford Centre for Gene Function
Mammalian Genetic Unit MRC | Harwell
http://www.stats.ox.ac.uk/~cholmes/

Solveig Sieberts
Rosetta Inpharmatics, LLC
401 Terry Avenue N
Seattle, WA 98109
Ph: (206) 802-6448
Fax: (206) 802-6411
Email: solveig_sieberts@merck.com

Jennifer Taylor
Jennifer Taylor is a researcher in the Bioinformatics Group at the
Wellcome Trust Centre for Human Genetics, University of Oxford. Her
research interests are high-throughput expression profiling and the
generation of integrated models of regulatory elements and expression to
further understand the regulation of gene expression in human disease
contexts. She completed her PhD using various computational and
experimental approaches towards the identification of candidate genes
for schizophrenia and cancer at the University of Queensland, and
completed post-doctoral appointments at the University of Queensland and
the Bioinformatics Group, Department of Statistics, University of Oxford.
As a member of Richard Mott's group in Oxford, she currently
collaborates with several research groups to analyse large genomics
projects.
Bioinformatics, Wellcome Trust Centre for Human Genetics
University of Oxford

Erin Conlon
Erin is an assistant professor in the Department of Mathematics and Statistics at the University of Massachusetts. Prior to her current position, she was a postdoctoral fellow at the University of Washington and Harvard University, studying statistical genetics and bioinformatics. Her doctoral degree is in Biostatistics from the University of Minnesota. Erin's research interests include microarray and DNA sequence analysis, Bayesian models for the analysis of genomic data and comparative genomics
Department of Mathematics and Statistics
Lederle Graduate Research Tower 1436
University of Massachusetts
Amherst, MA 01003
http://www.math.umass.edu/~conlon

Ernst Wit
Ernst Wit is heading the Medical Statistics Unit at Lancaster University. He has established himself firmly in the field of computational biology and statistical bioinformatics with his best-selling book "Statistics for Microarrays" (Wiley 2004). The book in particular, and all of his work in general, focusses on careful statistical design, analysis and inference, rather than ad hoc solutions of genetic data. Prof Wit research is focussed on modelling large-scale transcriptional data sets and integrating this with other data source. This is a formidable challenge and has involved considering structural network issues, the involvement of network topology in transcriptional kinetics and the intricate relationship between transcription and post-translational modifications. Wit is currently the Principle Investigator on several grants.
Heis an associate editor of Biostatistics and Applied Statistics and is a member of the Research Committee of the RSS.
Chair in Biometrics
Department of Maths and Stats
Lancaster University, UK