The elucidation of large-scale biological networks is currently a major challenge in systems biology. These networks include, for example, protein-protein interaction, metabolic, or regulatory networks, which describe various aspects of how life is organized at the molecular level. While these large-scale networks are slowly being discovered using various technologies, in silico methods to expand our current knowledge and predict missing edges are needed.
In this talk I will present some approaches we developed in the last few years to infer missing edges using supervised machine learning techniques, and illustrate their behaviour on several examples.