ArticleDatabase : the journal of biological databases and curation2013
Preliminary evaluation of the CellFinder literature curation pipeline for gene expression in kidney cells and anatomical parts.
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 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- An extensive review of tools for manual annotation of documents.Briefings in bioinformatics · 2021Review
- A context-based ABC model for literature-based discovery.PloS one · 2019Article
- Usage of cell nomenclature in biomedical literature.BMC bioinformatics · 2017Article
- Differential gene expression in disease: a comparison between high-throughput studies and the literature.BMC medical genomics · 2017Article
- Cell line name recognition in support of the identification of synthetic lethality in cancer from text.Bioinformatics (Oxford, England) · 2016Article
- Article
- TEES 2.2: Biomedical Event Extraction for Diverse Corpora.BMC bioinformatics · 2015Article
- Alkemio: association of chemicals with biomedical topics by text and data mining.Nucleic acids research · 2014Article
- CellFinder: a cell data repository.Nucleic acids research · 2014Article
- An analysis on the entity annotations in biological corpora.F1000Research · 2014Review
- Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis.Journal of the American Medical Informatics Association : JAMIAArticle
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomedical literature curation is the process of automatically and/or manually deriving knowledge from scientific publications and recording it into specialized databases for structured delivery to users. It is a slow, error-prone, complex, costly and, yet, highly important task. Previous experiences have proven that text mining can assist in its many phases, especially, in triage of relevant documents and extraction of named entities and biological events. Here, we present the curation pipeline of the CellFinder database, a repository of cell research, which includes data derived from literature curation and microarrays to identify cell types, cell lines, organs and so forth, and especially patterns in gene expression. The curation pipeline is based on freely available tools in all text mining steps, as well as the manual validation of extracted data. Preliminary results are presented for a data set of 2376 full texts from which >4500 gene expression events in cell or anatomical part have been extracted. Validation of half of this data resulted in a precision of ~50% of the extracted data, which indicates that we are on the right track with our pipeline for the proposed task. However, evaluation of the methods shows that there is still room for improvement in the named-entity recognition and that a larger and more robust corpus is needed to achieve a better performance for event extraction. Database URL: http://www.cellfinder.org/
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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.