Significant advances in computational methods can be gained through blinded benchmarking exercises, as evidenced by community progress in developing computational methods to predict protein structure from primary sequence. In 1993 when the "Critical Assessment of Techniques for Protein Structure Prediction" (CASP) exercise 1 () was launched, humans were often better at predicting protein structures than were computational methods. Leveraging high-quality and openly available experimental information in a well-organized database (the Worldwide Protein Data Bank [www.wwpdb.org]), in silico approaches gradually became increasingly capable of predicting protein structure. Very recently machine learning algorithms have been able to predict the structures of many (but not all) globular proteins as accurately as can be determined experimentally .