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Dataset Information

Detailed prediction of protein sub-nuclear localization.


ABSTRACT:

Background

Sub-nuclear structures or locations are associated with various nuclear processes. Proteins localized in these substructures are important to understand the interior nuclear mechanisms. Despite advances in high-throughput methods, experimental protein annotations remain limited. Predictions of cellular compartments have become very accurate, largely at the expense of leaving out substructures inside the nucleus making a fine-grained analysis impossible.

Results

Here, we present a new method (LocNuclei) that predicts nuclear substructures from sequence alone. LocNuclei used a string-based Profile Kernel with Support Vector Machines (SVMs). It distinguishes sub-nuclear localization in 13 distinct substructures and distinguishes between nuclear proteins confined to t

SUBMITTER: Littmann M 

PROVIDER: S-EPMC6480651 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature