A collection of intrinsic disorder characterizations from eukaryotic proteomes.
Intrinsically disordered proteins and protein regions lack a stable three-dimensional structure under physiological conditions. Several proteomic investigations of intrinsic disorder have been performed to date and have found disorder to be prevalent in eukaryotic proteomes. Here we present descriptive statistics of intrinsic disorder features for ten model eukaryotic proteomes that have been calculated from computational disorder prediction algorithms. The data descriptor also provides consensus disorder annotations as well as additional physical parameters relevant to protein disorder, and further provides protein existence information for all proteins included in our analysis. The complete datasets can be downloaded freely, and it is envisaged that they will be updated periodically with new proteomes and protein disorder prediction algorithms. These datasets will be especially useful for assessing protein disorder, and conducting novel analyses that advance our understanding of intrinsic disorder and protein structure.
Department of Molecular &Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan 48109-0622, USA.
Michael
M
Vincent
Department of Molecular &Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan 48109-0622, USA.|Department of Computational Medicine &Bioinformatics, University of Michigan Medical School, Michigan 48109-2218, USA.|Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, Michigan 48105-1912, USA.
Santiago
0000-0002-9477-3914
S
Schnell
D000465:Algorithms; D000818:Animals; D030562:Databases, Protein; D056890:Eukaryota; D006801:Humans; D064267:Intrinsically Disordered Proteins; D020543:Proteome
D064267:Intrinsically Disordered Proteins; D020543:Proteome