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Scientific Meeting Announcement - Wednesday 19th October 2011 2-5pm. Risk prediction modelling in genetic epidemiology Speakers: Cathryn Lewis (King's College London), David Balding (University College London), David Evans(University of Bristol) Pre-meeting introductory workshop on statistical genetics (10am-1pm) Delivered by: Jennifer Barrett and Marks Iles (University of Leeds) Venue: Hicks Building, University of Sheffield. Sponsors: Royal Statistical Society Medical Section Meeting, RSS Sheffield Local Group and RSS Young Statisticians Genetic epidemiology is a rapidly developing field within medical science. High-throughput genetic technologies applied to epidemiological collections have enabled large panels of genetic variations, densely covering the whole of the human genome, to be tested for association with disease risk. Such genome wide association studies have proved to be successful identifying many well replicated associations. However, as these identified genetic variants are frequently associated with modest changes in disease risk, attention is now turning to the development and implementation of multivariate risk prediction models. The meeting will focus on advances and challenges in the statistical methods required to develop and apply multivariate risk prediction models in the diagnostic and prognostic management of complex diseases. The workshop is aimed at career young statisticians and will provide an introduction and background to issues and terminology in statistical genetics. There is no charge to attend the meeting or the workshop, however it will assist our planning and booking appropriate lecture theatres if those intending to attend can email the organisers in advance. ([log in to unmask]). Travel directions to the University can be found below. http://www.sheffield.ac.uk/visitors/mapsandtravel The Hicks Building is building number 121 on the campus map A-Z. Meeting Organisers: Sara Hilditch, Nuala Sheehan, Dawn Teare. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.