SIB literature services : RESTful customizable search engines in biomedical literature, enriched with automatically mapped biomedical concepts

Gobeill, Julien (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale ; SIB Text Mining group, Swiss Institute of Bioinformatics, Geneva, Switzerland) ; Caucheteur, Déborah (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Michel, Pierre-André (SIB Text Mining group, Swiss Institute of Bioinformatics, Geneva, Switzerland) ; Mottin, Luc (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Pasche, Emilie (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale ; SIB Text Mining group, Swiss Institute of Bioinformatics, Geneva, Switzerland) ; Ruch, Patrick (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale ; SIB Text Mining group, Swiss Institute of Bioinformatics, Geneva, Switzerland)

Thanks to recent efforts by the text mining community, biocurators have now access to plenty of good tools and Web interfaces for identifying and visualizing biomedical entities in literature. Yet, many of these systems start with a PubMed query, which is limited by strong Boolean constraints. Some semantic search engines exploit entities for Information Retrieval, and/or deliver relevance-based ranked results. Yet, they are not designed for supporting a specific curation workflow, and allow very limited control on the search process. The Swiss Institute of Bioinformatics Literature Services (SIBiLS) provide personalized Information Retrieval in the biological literature. Indeed, SIBiLS allow fully customizable search in semantically enriched contents, based on keywords and/or mapped biomedical entities from a growing set of standardized and legacy vocabularies. The services have been used and favourably evaluated to assist the curation of genes and gene products, by delivering customized literature triage engines to different curation teams. SIBiLS (https://candy.hesge.ch/SIBiLS) are freely accessible via REST APIs and are ready to empower any curation workflow, built on modern technologies scalable with big data: MongoDB and Elasticsearch. They cover MEDLINE and PubMed Central Open Access enriched by nearly 2 billion of mapped biomedical entities, and are daily updated.


Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG - Genève
Institute:
CRAG - Centre de Recherche Appliquée en Gestion
Subject(s):
Sciences de l'information
Date:
2020-07
Pagination:
5 p.
Published in:
Nucleic Acids Research
Numeration (vol. no.):
2020, vol. 48, no W1, pp. W12-W16
DOI:
ISSN:
0305-1048
Appears in Collection:



 Record created 2020-07-20, last modified 2020-07-24

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