NoLogo: a new statistical model highlights the diversity and suggests new classes of Crm1-dependent nuclear export signals.

ABSTRACT:

Background

Crm1-dependent Nuclear Export Signals (NESs) are clusters of alternating hydrophobic and non-hydrophobic amino acid residues between 10 to 15 amino acids in length. NESs were largely thought to follow simple consensus patterns, based on which they were categorized into 6-10 classes. However, newly discovered NESs often deviate from the established consensus patterns. Thus, identifying NESs within protein sequences remains a bioinformatics challenge.

Results

We describe a probabilistic representation of NESs using a new generative model we call NoLogo that can account for a large diversity of NESs. Using this model to predict NESs, we demonstrate improved performance over PSSM and GLAM2 models, but do not achieve the performance of the state-of-the-art NES predicto

SUBMITTER: Liku ME 

PROVIDER: S-EPMC5828312 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature