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On the Need to Develop Guidelines for Characterizing and Reporting Intrinsic Disorder in Proteins
Author(s) -
Vincent Michael,
Uversky Vladimir N.,
Schnell Santiago
Publication year - 2019
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201800415
Subject(s) - field (mathematics) , data science , set (abstract data type) , computer science , intrinsically disordered proteins , proteome , management science , bioinformatics , biology , engineering , mathematics , biochemistry , pure mathematics , programming language
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. This viewpoint explores a handful of these reasons, including standardizing nomenclature to improve communication, rigor and reproducibility, and making it easier for newcomers to enter the field. An approach for reporting predicted disorder in single proteins with respect to whole proteomes is discussed. The suggestions are not intended to be formulaic; they should be viewed as a starting point to establish guidelines for interpreting and reporting computational protein disorder predictions.