DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.

ABSTRACT: There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this

SUBMITTER: Motion GB 

PROVIDER: S-EPMC4678848 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature