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Title: Taxon-specific contributions to silica production in natural diatom assemblages: Taxon-specific Si production
Authors:
 ;  ;  ;  
Publication Date:
NSF-PAR ID:
10067035
Journal Name:
Limnology and Oceanography
Volume:
63
Issue:
3
Page Range or eLocation-ID:
1056 to 1075
ISSN:
0024-3590
Publisher:
Wiley Blackwell (John Wiley & Sons)
Sponsoring Org:
National Science Foundation
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  1. Abstract Motivation Many protein function databases are built on automated or semi-automated curations and can contain various annotation errors. The correction of such misannotations is critical to improving the accuracy and reliability of the databases. Results We proposed a new approach to detect potentially incorrect Gene Ontology (GO) annotations by comparing the ratio of annotation rates (RAR) for the same GO term across different taxonomic groups, where those with a relatively low RAR usually correspond to incorrect annotations. As an illustration, we applied the approach to 20 commonly-studied species in two recent UniProt-GOA releases and identified 250 potential misannotations in the 2018-11-6 release, where only 25% of them were corrected in the 2019-6-3 release. Importantly, 56% of the misannotations are “Inferred from Biological aspect of Ancestor (IBA)” which is in contradiction with previous observations that attributed misannotations mainly to “Inferred from Sequence or structural Similarity (ISS)”, probably reflecting an error source shift due to the new developments of function annotation databases. The results demonstrated a simple but efficient misannotation detection approach that is useful for large-scale comparative protein function studies. Availability https://zhanglab.ccmb.med.umich.edu/RAR Supplementary information Supplementary data are available at Bioinformatics online.