DISOselect: Disorder predictor selection at the protein level.

ABSTRACT: The intense interest in the intrinsically disordered proteins in the life science community, together with the remarkable advancements in predictive technologies, have given rise to the development of a large number of computational predictors of intrinsic disorder from protein sequence. While the growing number of predictors is a positive trend, we have observed a considerable difference in predictive quality among predictors for individual proteins. Furthermore, variable predictor performance is often inconsistent between predictors for different proteins, and the predictor that shows the best predictive performance depends on the unique properties of each protein sequence. We propose a computational approach, DISOselect, to estimate the predictive performance of 12 selected predictors f

SUBMITTER: Katuwawala A 

PROVIDER: S-EPMC6933862 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature