NoGOA: predicting noisy GO annotations using evidences and sparse representation.

ABSTRACT:

Background

Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations. Given the wide application of annotations, however, how to identify noisy annotations is an important but yet seldom studied open problem.

Results

We introduce a novel approach called NoGOA to predict noisy annotations. NoGOA applies sparse representation

SUBMITTER: Yu G 

PROVIDER: S-EPMC5521088 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature