ICTP-ICTS Winter School on Quantitative Systems Biology | (smr 3755)
Starts 5 Dec 2022
Ends 16 Dec 2022
Central European Time
Giambiagi Lecture Hall (AGH)
Riva Massimiliano e Carlotta, Grignano
I - 34151 Trieste (Italy)
An ICTP Hybrid Meeting. You can submit your application for participation in presence or online.
Machine Learning is increasingly being used in biology, as also in other physical and life sciences, to build predictive models of underlying processes.
This school will combine the knowledge of biologists who work with large and heterogeneous data, of physicists who are experts at modelling such complexity, and of machine learning experts who bring in state-of-the-art methods in statistics. This integrated approach is essential to learn how to tackle these issues and gain a better understanding of key phenomena in biology.
G. CARAVAGNA, University of Trieste, Italy
P. CHAUDHARI, University of Pennsylvania, USA
S. MUKHERJEE, MPG Leipzig, Germany
E. PIASINI, SISSA, Italy
R. POTESTIO, University of Trento, Italy
G. SCHWEIKERT, University of Dundee, UK
G. TKACIK, IST, Austria
C. TOMASETTI, City of Hope, Los Angeles, USA
C. VALLEJOS, University of Edinburgh, UK
Scientific Advisory Committee:
V. BALASUBRAMANIAN, University of Pennsylvania, USA
A. CELANI, ICTP, Italy
S. JAIN, University of Delhi, India
V.K. KRISHNAMURTHY, ICTS, Bangalore, India
M. MARSILI, ICTP, Italy
M. THATTAI, National Centre for Biological Sciences, India
Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee.