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Preliminary evaluation of the CellFinder literature curation pipeline for gene expression in kidney cells and anatomical parts

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Item Type:Article
Title:Preliminary evaluation of the CellFinder literature curation pipeline for gene expression in kidney cells and anatomical parts
Creators Name:Neves, M. and Damaschun, A. and Mah, N. and Lekschas, F. and Seltmann, S. and Stachelscheid, H. and Fontaine, J.F. and Kurtz, A. and Leser, U.
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/
Keywords:Computational Biology, Data Mining, Databases as Topic, Gene Expression Regulation, Kidney, Publications, Reproducibility of Results, Software, Statistics as Topic
Source:Database
ISSN:1758-0463
Volume:2013
Number:2013
Page Range:bat020
Date:18 April 2013
Official Publication:https://doi.org/10.1093/database/bat020
PubMed:View item in PubMed

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