Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection.

ABSTRACT: Meta-predictors make predictions by organizing and processing the predictions produced by several other predictors in a defined problem domain. A proficient meta-predictor not only offers better predicting performance than the individual predictors from which it is constructed, but it also relieves experimentally researchers from making difficult judgments when faced with conflicting results made by multiple prediction programs. As increasing numbers of predicting programs are being developed in a large number of fields of life sciences, there is an urgent need for effective meta-prediction strategies to be investigated. We compiled four unbiased phosphorylation site datasets, each for one of the four major serine/threonine (S/T) protein kinase families-CDK, CK2, PKA and PKC. Using these d

SUBMITTER: Wan J 

PROVIDER: S-EPMC2275094 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature