ArticleNucleic acids research2020
SIB Literature Services: RESTful customizable search engines in biomedical literature, enriched with automatically mapped biomedical concepts.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- The missing link in FAIR data policy: biodata resources in life sciences.Scientific data · 2026Article
- Enhancing the SIB Literature Services (SIBiLS) with annotations to support biocuration.Database : the journal of biological databases and curation · 2026Article
- DisProt in 2026: enhancing intrinsically disordered proteins accessibility, deposition, and annotation.Nucleic acids research · 2026Article
- Empowering biological knowledgebases: advances in human-in-the-loop AI-driven literature curation.Bioinformatics advances · 2026Review
- Gender and geographical bias in the editorial decision-making process of biomedical journals: a case-control study.BMJ evidence-based medicine · 2025Article
- Unlocking the potential of PubMed Central supplementary data files.Bioinformatics advances · 2025Article
- Ensemble of deep learning language models to support the creation of living systematic reviews for the COVID-19 literature.Systematic reviews · 2023Article
- Assessing the use of supplementary materials to improve genomic variant discovery.Database : the journal of biological databases and curation · 2023Article
- COVoc and COVTriage: novel resources to support literature triage.Bioinformatics (Oxford, England) · 2023Article
- Variomes: a high recall search engine to support the curation of genomic variants.Bioinformatics (Oxford, England) · 2022Article
- LitSuggest: a web-based system for literature recommendation and curation using machine learning.Nucleic acids research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.