How can modelers restore confidence in systems and computational biology? Systems biology, some have claimed ( 1 ), attempts the impossible and is doomed to fail. Possible definitions abound, but systems biology is widely understood to be an approach for studying the behavior of systems of interacting biological components that combines experiments with computational and mathematical reasoning. Modeling complex systems occurs throughout the sciences, so it may not be immediately clear why it should attract greater skepticism in molecular and cell biology than in other scientific disciplines. The way in which biological models are often presented and interpreted (and overinterpreted) may be partly to blame. As with experimental results, the key to successfully reporting a mathematical model is to provide an honest appraisal and representation of uncertainty in the model's predictions, parameters, and (where appropriate) in the structure of the model itself.