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ANC SEMINAR: Data Mining for Personalized Medicine, Karsten Borgwardt, Dept. Biosystems, ETH Zurich

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Chair: Guido Sanguinetti

  • ANC/DTC Seminar
When Apr 28, 2015
from 11:00 AM to 12:00 PM
Where IF Room 4.31/4.33
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Over the last decade, enormous technological advances have allowed us to record the health state of an individual patient down to the molecular level of gene activity and genomic information — even sequencing a patient’s genome for less than 1000 dollars is within reach. However, the ultimate hope to use all this information for personalized medicine, that is to tailor medical treatment to the needs of an individual, remains largely unfulfilled. To turn the vision of personalized medicine into reality, many methodological problems remain to be solved: there is a lack of methods that allow us to gain a causal understanding of the underlying disease mechanisms, including gene-gene and gene-environment interactions. Similarly, there is an urgent need for integration of the heterogeneous patient data currently available, for improved and robust biomarker discovery for disease diagnosis, prognosis and therapy outcome prediction. The field of data mining, which tries to detect patterns, rules and statistical dependencies in large datasets, has also witnessed dramatic progress over the last decade and has had a profound impact on the Internet. Amongst others, advanced methods for high-dimensional feature selection, causality inference, and data integration have been developed or are topics of current research. These techniques address many of the key methodological challenges that personalized medicine faces today and keep it from rising to the next level. In this talk, we will describe the challenges and opportunities for data mining in personalized medicine and we will present our recent research results in this direction.


Karsten Borgwardt is Professor of Data Mining at the Department of Biosystems at ETH Zurich since June 2014. He received the Heinz Schwärtzel Dissertation Award in 2007, the NIPS Outstanding Paper Award in 2009, the Krupp Award for Young Professors in 2013, and a Starting Grant from the ERC-backup scheme of the Swiss National Science Foundation in 2014. Since 2013, he is heading the European Marie Curie Network on “Machine Learning for Personalized Medicine” with 12 partner labs in 8 countries (For his full cv and further information see:


Lunch will be provided