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Usage of cell nomenclature in biomedical literature
BACKGROUND: Cell lines and cell types are extensively studied in biomedical research yielding to a significant amount of publications each year. Identifying cell lines and cell types precisely in publications is crucial for science reproducibility and knowledge integration. There are efforts for sta...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763300/ https://www.ncbi.nlm.nih.gov/pubmed/29322912 http://dx.doi.org/10.1186/s12859-017-1978-0 |
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author | Kafkas, Şenay Sarntivijai, Sirarat Hoehndorf, Robert |
author_facet | Kafkas, Şenay Sarntivijai, Sirarat Hoehndorf, Robert |
author_sort | Kafkas, Şenay |
collection | PubMed |
description | BACKGROUND: Cell lines and cell types are extensively studied in biomedical research yielding to a significant amount of publications each year. Identifying cell lines and cell types precisely in publications is crucial for science reproducibility and knowledge integration. There are efforts for standardisation of the cell nomenclature based on ontology development to support FAIR principles of the cell knowledge. However, it is important to analyse the usage of cell nomenclature in publications at a large scale for understanding the level of uptake of cell nomenclature in literature by scientists. In this study, we analyse the usage of cell nomenclature, both in Vivo, and in Vitro in biomedical literature by using text mining methods and present our results. RESULTS: We identified 59% of the cell type classes in the Cell Ontology and 13% of the cell line classes in the Cell Line Ontology in the literature. Our analysis showed that cell line nomenclature is much more ambiguous compared to the cell type nomenclature. However, trends indicate that standardised nomenclature for cell lines and cell types are being increasingly used in publications by the scientists. CONCLUSIONS: Our findings provide an insight to understand how experimental cells are described in publications and may allow for an improved standardisation of cell type and cell line nomenclature as well as can be utilised to develop efficient text mining applications on cell types and cell lines. All data generated in this study is available at https://github.com/shenay/CellNomenclatureStudy. |
format | Online Article Text |
id | pubmed-5763300 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57633002018-01-17 Usage of cell nomenclature in biomedical literature Kafkas, Şenay Sarntivijai, Sirarat Hoehndorf, Robert BMC Bioinformatics Research BACKGROUND: Cell lines and cell types are extensively studied in biomedical research yielding to a significant amount of publications each year. Identifying cell lines and cell types precisely in publications is crucial for science reproducibility and knowledge integration. There are efforts for standardisation of the cell nomenclature based on ontology development to support FAIR principles of the cell knowledge. However, it is important to analyse the usage of cell nomenclature in publications at a large scale for understanding the level of uptake of cell nomenclature in literature by scientists. In this study, we analyse the usage of cell nomenclature, both in Vivo, and in Vitro in biomedical literature by using text mining methods and present our results. RESULTS: We identified 59% of the cell type classes in the Cell Ontology and 13% of the cell line classes in the Cell Line Ontology in the literature. Our analysis showed that cell line nomenclature is much more ambiguous compared to the cell type nomenclature. However, trends indicate that standardised nomenclature for cell lines and cell types are being increasingly used in publications by the scientists. CONCLUSIONS: Our findings provide an insight to understand how experimental cells are described in publications and may allow for an improved standardisation of cell type and cell line nomenclature as well as can be utilised to develop efficient text mining applications on cell types and cell lines. All data generated in this study is available at https://github.com/shenay/CellNomenclatureStudy. BioMed Central 2017-12-21 /pmc/articles/PMC5763300/ /pubmed/29322912 http://dx.doi.org/10.1186/s12859-017-1978-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kafkas, Şenay Sarntivijai, Sirarat Hoehndorf, Robert Usage of cell nomenclature in biomedical literature |
title | Usage of cell nomenclature in biomedical literature |
title_full | Usage of cell nomenclature in biomedical literature |
title_fullStr | Usage of cell nomenclature in biomedical literature |
title_full_unstemmed | Usage of cell nomenclature in biomedical literature |
title_short | Usage of cell nomenclature in biomedical literature |
title_sort | usage of cell nomenclature in biomedical literature |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763300/ https://www.ncbi.nlm.nih.gov/pubmed/29322912 http://dx.doi.org/10.1186/s12859-017-1978-0 |
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