EDITORIAL Ten Simple Rules for a Community Computational Challenge

In science, the relationship between methods and discovery is symbiotic. As we discover more, we are able to construct more precise and sensitive tools and methods that enable further dis-covery. With better lens crafting came microscopes, and with them the discovery of living cells. In the last 40 years, advances in molecular biology, statistics, and computer science have ush-ered in the field of bioinformatics and the genomic era. Computational scientists enjoy developing new methods, and the community encourages them to do so. Indeed, the editorial guidelines for PLOS Computational Biology require manu-scripts to apply novel methods. However, it is often confusing to know which method to choose: which method is best? And, in this context, what does “best”mean? To help choose an appropriate method for a particular task, scientists often form communi-ty-based challenges for the unbiased evaluation of methods in a given field. These challenges help evaluate existing and novel methods, while helping to coalesce a community and leading to new ideas and collaborations. In computational biology, the first of these challenges was arguably the Critical Assess-ment of protein Structure Prediction, or CASP [1], whose goal is to evaluate methods for pre