Machine Learning Frontiers in Precision Medicine
We are coordinating the Marie Curie Innovative Training Network entitled "Machine Learning Frontiers in Precision Medicine" bringing together leading European research institutes in machine learning and statistical genetics, both from the private and public sector. We train 14 early stage researchers who will apply machine learning methods to health data. The goal is to reveal new insights into disease mechanisms and therapy outcomes and to exploit the findings for precision medicine, which hopes to offer personalized preventive care and therapy selection for each patient.
Network partners
The MLFPM network consists of the following partner institutions and PIs: ETH Zürich (Karsten Borgwardt, Caroline Uhler), University of Liege (Kristel Van Steen), Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (Bertram Müller-Myhsok, Bernhard Schölkopf and Gabriele Schweikert), Siemens Healthcare GmbH (Tobias Heimann and Volker Tresp), University of Tartu (Krista Fischer), STACC (Jaak Vilo), Fundación Pública Andaluza Progreso y Salud (Joaquin Dopazo), Universidad Carlos III de Madrid (Antonio Artés), ARMINES (Chloé-Agathe Azencott), Université Paris Descartes (Florence Demenais), Qlucore (Carl-Johan Ivarsson and Magnus Fontes), IBM Israel (Tal El-Hay and Michal Rosen-Zvi), Pharmatics (Felix Agakov) and Roche (Antonia Stank).
Funding
The total funding for MLFPM is EUR 3 638 275,56.
Two MLFPM fellows at MLCB lab
Two of the 14 Early Stage Researchers will conduct their work at the MLCB lab. ESR1 is working on "Machine Learning for Biological Network Analysis", and ESR2 is working on the project "Machine Learning and Causal Inference to Optimize Genomic Interventions using Disease State Representations".
More information is available on the MLFPM webpage: external page https://mlfpm.eu
