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High Dimensional Statistics in Biology

31st March 2008 to 4th April 2008

Organisers: Peter Bickel (UC Berkeley), Ewan Birney (EBI), Wolfgang Huber (EBI) and Richard Durbin (Sanger Institute)

Workshop Theme

The study of biological systems has been revolutionized by the advent of large scale systematic data gathering. Led by the Human Genome project, but extending across many biological disciplines, an increasing number of large and complex datasets has been developed which inform our biological understanding of both the normal workings of organisms in biology and processes which cause disease.

The analysis of these datasets ,which has become an increasingly important part of biology, poses a number of interesting statistical problems, largely driven by the complex inter-relationships between measurements .The size and complexity of these datasets make even adaptation of existing statistical techniques to biological problems novel . In some cases, the development of entirely new statistical methods is necessary. Methods developed and developing for high dimensional (large p) and possibly small sample size (small n) inference seem particularly germane. So do methods such as FDR for simultaneously testing many hypotheses.

In this workshop we aim to provide a collegial, inter disciplinary group of both statisticians and biologists to exchanges ideas and challenges at the Newton Institute in Cambridge UK. Drawing on both nearby expertise at the Hinxton Campus (the EBI and the Sanger Institute) and worldwide expertise in statistics the workshop will involve 45-50 minute overview talks from both biologists and statisticians and less structured, collaboration based time as well as a possible poster session


University of Cambridge Research Councils UK
    Clay Mathematics Institute The Leverhulme Trust London Mathematical Society Microsoft Research NM Rothschild and Sons