Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset.

ABSTRACT:

Background

Algorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable.

Results

First, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended de

SUBMITTER: Sirota FL 

PROVIDER: S-EPMC2822529 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature