Bioinformatics is an application domain where information is naturally represented in terms of relations between heterogenous objects. Modern experimentation and data acquisition techniques allow the study of complex interactions in biological systems. This raises interesting challenges for machine learning and data mining researchers, as the amount of data is huge, some information can not be observed, and measurements may be noisy. This report presents a review on the ACM SIGKDD 2009 Workshop on Statistical Relational Learning and Mining in Bioinformatics (StReBio'09) which was held in Paris on June 28th, 2009. The aim of this workshop was to provide a forum to share challenges, results and ideas at the frontier between the field of statistical relational learning and the field of bioinformatics.
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