Bologna Winter School 2009 - Machine Learning and Computational Biology: New paradigms for a new science - Bologna, February 2-6, 2009

In the post-genome era the vast mass of biological data is growing more than ever before. The creation of automatic and “intelligent” tools that can help to organize, analyze and unravel the underlying information is one of the most wonted and less solved problems in biological sciences. Pushing forward current boundaries between existing solutions and innovative ideas is the only way to fill the gap between what we know and what we understand. Moreover, great expectations have been generated in different fields by the increasing role and impact of computer science in processing and analyzing terabytes of data. Machine Learning methods are among the most successful computational tools that have been introduced so far in Computational Biology. The 10^th edition of the Bologna Winter School in Bioinformatics will provide comprehensive overview of different Machine Learning fields in the light of their common probabilistic framework. The programme starts with an introduction to Graphical Models that are the unifying formalism on which most of the current machine learning methods can be described. Dynamical Bayesian networks with specific application to the reconstruction of biological networks will be then discussed. An introduction to the hidden Markov models will explain the details of the these highly successful probabilistic models. Finally two days are devoted at the Statistical learning models such as Support Vector Machines and andvanced Neural Networks. These different one-morning tutorials will be followed by general lectures describing the most recent successful applications in Computational Biology.