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Database (Oxford). 2016 Jul 3;2016. pii: baw098. doi: 10.1093/database/baw098. Print 2016.

neXtA5: accelerating annotation of articles via automated approaches in neXtProt.

Author information

1
BiTeM Group, University of Applied Sciences, Western Switzerland-HEG Genève, Information Science Department SIB Text Mining, Swiss Institute of Bioinformatics luc.mottin@hesge.ch patrick.ruch@hesge.ch.
2
BiTeM Group, University of Applied Sciences, Western Switzerland-HEG Genève, Information Science Department SIB Text Mining, Swiss Institute of Bioinformatics.
3
Calipho Group, Swiss Institute of Bioinformatics.

Abstract

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein-protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline.Available on: http://babar.unige.ch:8082/neXtA5Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp.

PMID:
27374119
PMCID:
PMC4930835
DOI:
10.1093/database/baw098
[Indexed for MEDLINE]
Free PMC Article

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