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The Dialogue for Reverse Engineering Assessments and Methods (DREAM) grew as a community effort to catalyze discussion about the design, application, and assessment of systems biology models through annual conferences and reverse-engineering and predictive modeling challenges. The various challenges, based on anonymized data sets, tested participants in network inference and prediction of measurements. These challenges encompass a variety of problems at the core of systems biology, such as network inference, determination of diagnostic signatures, prediction of outcomes of biological systems as a result of perturbations, transcriptional dynamics, protein-protein recognition, etc. The collection summarizes the lessons learned by the DREAM community and provides a much-needed context for interpreting claims of efficacy of algorithms described in the scientific literature.