Together with Blaz Zupan we organize a tutorial on data fusion at the Basel Computational Biology Conference ([BC]^2). The tutorial is targeted at computational scientists, data mining researchers and molecular biologists interested in large-scale data integration and predictive modeling.

In the tutorial we focus on collective latent factor models, which have gained popularity in recent years through many successful applications in integrative predictive modeling. We have prepared a series of short lecture notes, which provide the intuition and mathematics behind the algorithms, explain why factorization approaches are suitable when collectively analyzing many heterogeneous data sets, and contain a number of case studies taken from recommendation systems, functional genomics, molecular and systems biology. We demonstrate several recent methodological advancements in hands-on sessions using Orange and its Data Fusion Add-on.

This tutorial would not be possible without the great support by the Bioinformatics Laboratory at University of Ljubljana.