Machine Learning for Personalized Medicine

Marie-Curie Action: "Initial Training Networks"

ESHG Workshop 2016

Big data in human genetics: opportunities and challenges?

Workshop at the European Human Genetics Conference 2016 (ESHG 2016)

  • May 21, 2016
  • 10h30-12h
  • Convention Centre Barcelona (CCIB), Willy Brandt Square 11-14, 08019 Barcelona
  • Room 112

Personalized Medicine has received increasing interest over the last years, not only from the scientific community but also from governments and the general public. Its aim is to combine genetic, clinical, and environmental data to improve medical diagnosis and disease treatment, tailored to each individual. In this workshop we give an overview of the main challenges in this field, e.g., how to deal with patient heterogeneity in a highly dimensional space, how to obtain easy-to-interpret models for highly complex biological scenarios, and how to generalize/validate discoveries and guarantee their replicability. The audience is invited to join us in a brainstorming exercise to overcome some of these challenges. Cutting-edge seed idea solutions are provided from a Machine Learning and Statistical Genetics points of view.

The workshop is organised by the Intitial Training Network "Machine Learning for Personalized Medicine"

Programme:

Introduction to Personalized Medicine: challenges and opportunities
(Kristel Van Steen, GIGA-R Medical Genomics –BIO3 Unit, University of Liège, Liège, Belgium)

Selected presentations on Big Data analysis problems, focusing on predication and data exploration 
(Marie Curie Initial Training Network “Machine Learning for Personalized Medicine”)

Prediction

 

Data Exploration

 Take-home messages and future perspectives for human geneticists
(Bertram Müller-Myhsok, MPI for psychiatry - Statistical Genetics, Munich, Germany & Institute of Translational Medicine, University of Liverpool, UK)

 

Registration: This workshop is part of the European Human Genetics Conference 2016. In order to participate,  registration for ESHG 2016 is required. Please register here

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