ArticleDatabase : the journal of biological databases and curation2013
BioC: a minimalist approach to interoperability for biomedical text processing.
Article in Database : the journal of biological databases and curation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 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
114 citing papers in PubMed.
- What Do Biomedical NER and Entity Linking Benchmarks Measure? A Corpus-Centric Diagnostic Framework.ArXiv · 2026Article
- Cell phenotypes in the biomedical literature: a systematic analysis and text mining corpus.bioRxiv : the preprint server for biology · 2026Article
- A FAIR gold-standard benchmark for geographic entity recognition in cancer genomics literature for biomedical NLP.Bioinformatics advances · 2026Article
- Large language models in food and nutrition science: Opportunities, challenges, and the case of FoodyLLM.Current research in food science · 2026Article
- Curation and Extraction of Drug-Related Entities from Reddit Platform.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- Article
- Evaluating Language Models for Biomedical Fact-Checking: A Benchmark Dataset for Cancer Variant Interpretation Verification.bioRxiv : the preprint server for biology · 2025Article
- Extracting post-acute sequelae of SARS-CoV-2 infection symptoms from clinical notes via hybrid natural language processing.npj health systems · 2025Article
- LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery.Nucleic acids research · 2025Article
- AutoPM3: enhancing variant interpretation via LLM-driven PM3 evidence extraction from scientific literature.Bioinformatics (Oxford, England) · 2025Article
- Detection of patient metadata in published articles for genomic epidemiology using machine learning and large language models.medRxiv : the preprint server for health sciences · 2025Article
- Integrating AI-powered text mining from PubTator into the manual curation workflow at the Comparative Toxicogenomics Database.Database : the journal of biological databases and curation · 2025Article
- A retrieval-augmented knowledge mining method with deep thinking LLMs for biomedical research and clinical support.GigaScience · 2025Article
- From literature to biodiversity data: mining arthropod organismal traits with machine learning.Biodiversity data journal · 2025Article
- Is metadata of articles about COVID-19 enough for multilabel topic classification task?Database : the journal of biological databases and curation · 2024Article
- Dataset from a human-in-the-loop approach to identify functionally important protein residues from literature.Scientific data · 2024Article
- EnzChemRED, a rich enzyme chemistry relation extraction dataset.Scientific data · 2024Article
- The biomedical relationship corpus of the BioRED track at the BioCreative VIII challenge and workshop.Database : the journal of biological databases and curation · 2024Article
- The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII.Database : the journal of biological databases and curation · 2024Article
- PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge.Nucleic acids research · 2024Article
54 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
A vast amount of scientific information is encoded in natural language text, and the quantity of such text has become so great that it is no longer economically feasible to have a human as the first step in the search process. Natural language processing and text mining tools have become essential to facilitate the search for and extraction of information from text. This has led to vigorous research efforts to create useful tools and to create humanly labeled text corpora, which can be used to improve such tools. To encourage combining these efforts into larger, more powerful and more capable systems, a common interchange format to represent, store and exchange the data in a simple manner between different language processing systems and text mining tools is highly desirable. Here we propose a simple extensible mark-up language format to share text documents and annotations. The proposed annotation approach allows a large number of different annotations to be represented including sentences, tokens, parts of speech, named entities such as genes or diseases and relationships between named entities. In addition, we provide simple code to hold this data, read it from and write it back to extensible mark-up language files and perform some sample processing. We also describe completed as well as ongoing work to apply the approach in several directions. Code and data are available at http://bioc.sourceforge.net/. Database URL: http://bioc.sourceforge.net/
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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.