In the last decades intrinsic disorder has emerged as a prevalent property amongst proteins expressed by organisms in all kingdoms of life. Improving the characterization of protein disorder will allow us to better understand its physiological role and function. Since the early 2000s, numerous computational tools have been created and used to predict intrinsic disorder in proteins. At present, the output from these algorithms is difficult to interpret in the absence of standards or references for comparison. There are many reasons to establish a set of standard-based guidelines to evaluate computational protein disorder predictions with rigor and reproducibility.

IN our laboratory, we are developing, Disorder Atlas, a web-based tool that facilitates the interpretation of intrinsic disorder predictions using proteome-based descriptive statistics.