ArticleBMC bioinformatics2014
OntoGene web services for biomedical text mining.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Integrating text mining and knowledge graph to enhance biopharmaceutical process optimization.PloS one · 2026Article
- An extensive review of tools for manual annotation of documents.Briefings in bioinformatics · 2021Review
- Article
- Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives.Human genetics · 2019Review
- OGER++: hybrid multi-type entity recognition.Journal of cheminformatics · 2019Article
- MER: a shell script and annotation server for minimal named entity recognition and linking.Journal of cheminformatics · 2018Article
- ezTag: tagging biomedical concepts via interactive learning.Nucleic acids research · 2018Article
- Entity recognition in the biomedical domain using a hybrid approach.Journal of biomedical semantics · 2017Article
- Text Mining in Biomedical Domain with Emphasis on Document Clustering.Healthcare informatics research · 2017Review
- Strategies towards digital and semi-automated curation in RegulonDB.Database : the journal of biological databases and curation · 2017Article
- PubMedPortable: A Framework for Supporting the Development of Text Mining Applications.PloS one · 2016Article
- neXtA5: accelerating annotation of articles via automated approaches in neXtProt.Database : the journal of biological databases and curation · 2016Article
- Building a glaucoma interaction network using a text mining approach.BioData mining · 2016Article
- NETTAB 2013: Semantic, social, and mobile applications for bioinformatics and biomedical laboratories.BMC bioinformatics · 2014Article
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
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.
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.