Scientific article
Open access

neXtA5: accelerating annotation of articles via automated approaches in neXtProt

Published inDatabase, vol. 2016
Publication date2016

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.

Research group
  • Swiss National Science Foundation - 153437
Citation (ISO format)
MOTTIN, Luc et al. neXtA5: accelerating annotation of articles via automated approaches in neXtProt. In: Database, 2016, vol. 2016. doi: 10.1093/database/baw098
Main files (1)
Article (Published version)
ISSN of the journal1758-0463

Technical informations

Creation08/11/2016 10:15:00 AM
First validation08/11/2016 10:15:00 AM
Update time03/15/2023 12:36:39 AM
Status update03/15/2023 12:36:39 AM
Last indexation10/19/2023 1:45:20 AM
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