Discriminative motif finding for predicting protein subcellular localization.

ABSTRACT: Many methods have been described to predict the subcellular location of proteins from sequence information. However, most of these methods either rely on global sequence properties or use a set of known protein targeting motifs to predict protein localization. Here, we develop and test a novel method that identifies potential targeting motifs using a discriminative approach based on hidden Markov models (discriminative HMMs). These models search for motifs that are present in a compartment but absent in other, nearby, compartments by utilizing an hierarchical structure that mimics the protein sorting mechanism. We show that both discriminative motif finding and the hierarchical structure improve localization prediction on a benchmark data set of yeast proteins. The motifs identified can be

SUBMITTER: Lin TH 

PROVIDER: S-EPMC3050600 | biostudies-literature | 2011 Mar-Apr

REPOSITORIES: biostudies-literature