ESHG Symposium 2016

Posted by: MLPM-Admin 8 years ago

Join us for this exciting symposium in Barcelona! Registration for external participants is now closed.

Machine learning is a powerful tool to analyze large, high-dimensional biomedical data sets (e.g. genetic, proteomic, or transcriptomic data). The objective is to find patterns in the deep sea of data that are significantly related to the development or progression of diseases or play a role in individual drug responses. Ultimately, machine learning algorithms are developed to provide physicians and other health professionals with clinical decision support.

At our conference we will bring together experts from this highly interdisciplinary field: human geneticists, bioinformaticians and machine learners will discuss recent research results and benefit from each others expertise.

"Machine Learning for Personalized Medicine - The alliance of Genetics, Bioinformatics and Data Mining to decipher multifactorial phenotypes"

Satellite Symposium of the European Human Genetics Conference 2016

CONFIRMED SPEAKERS:

Robert Castelo "Systems genetics with graphical Markov models"
Universitat Pompeu Fabra (UPF)
Barcelona Biomedical Research Park (PRBB)

Krista Fischer (Title TBA)
University of Tartu, Tartu, Estonia

Lude Franke "Identifying drug-targetable key drivers of disease"

University of Groningen, The Netherlands

Luis Serrano "Integrative and quantitative analysis of disease mutations in the RAS-RAF-MEK-ERK pathway and implications for personalized medicine"

Centre for Genomic Regulation (CRG), Barcelona, Spain

Terry Speed "Removing Unwanted Variation in Machine Learning for Personalized Medicine"

Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Australia

Alfonso Valencia (Title of talk TBA)

Structural Computational Biology Group, Spanish National Cancer Research Centre (CNIO), Madrid

Let's meet in one of the MOST FASCINATING cities of Spain!

More information and registration

Machine Learning for Personalized Medicine

Marie-Curie Action: "Initial Training Networks"