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BMC Bioinformatics. 2013 Mar 22;14:104. doi: 10.1186/1471-2105-14-104.

Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

Author information

1
Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, 1 Michel Servet, 1211 Geneva 4, Switzerland. anne-lise.veuthey@isb-sib.ch

Abstract

BACKGROUND:

The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB.

RESULTS:

The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments.

CONCLUSIONS:

The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/.

PMID:
23517090
PMCID:
PMC3660268
DOI:
10.1186/1471-2105-14-104
[Indexed for MEDLINE]
Free PMC Article

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