Prediction of kinase-specific phosphorylation sites using conditional random fields.

ABSTRACT:

Motivation

Phosphorylation is a crucial post-translational protein modification mechanism with important regulatory functions in biological systems. It is catalyzed by a group of enzymes called kinases, each of which recognizes certain target sites in its substrate proteins. Several authors have built computational models trained from sets of experimentally validated phosphorylation sites to predict these target sites for each given kinase. All of these models suffer from certain limitations, such as the fact that they do not take into account the dependencies between amino acid motifs within protein sequences in a global fashion.

Results

We propose a novel approach to predict phosphorylation sites from the protein sequence. The method uses a positive dataset to train a cond

SUBMITTER: Dang TH 

PROVIDER: S-EPMC2639296 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature