Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

neXtA5

General information

URL: http://babar.unige.ch:8082/neXtA5
Full name:
Description: neXtA5 prioritizes the literature for specific curation requirements
Year founded: 2016
Last update: 2016-07-02
Version:
Accessibility:
Accessible
Country/Region: Sweden

Classification & Tag

Data type:
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Swiss Institute of Bioinformatics
Address: BiTeM Group, University of Applied Sciences, Western Switzerland-HEG Genève, Information Science Department SIB Text Mining
City: Geneve
Province/State:
Country/Region: Sweden
Contact name (PI/Team): Luc Mottin
Contact email (PI/Helpdesk): luc.mottin@hesge.ch

Publications

27374119
neXtA5: accelerating annotation of articles via automated approaches in neXtProt. [PMID: 27374119]
Mottin L, Gobeill J, Pasche E, Michel PA, Cusin I, Gaudet P, Ruch P.

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. © The Author(s) 2016. Published by Oxford University Press.

Database (Oxford). 2016:2016() | 8 Citations (from Europe PMC, 2026-04-04)

Ranking

All databases:
5627/6932 (18.84%)
Literature:
472/577 (18.371%)
5627
Total Rank
7
Citations
0.7
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Record metadata

Created on: 2017-03-28
Curated by:
Shixiang Sun [2017-03-28]