Usage of cell nomenclature in biomedical literature

Handle URI:
http://hdl.handle.net/10754/626451
Title:
Usage of cell nomenclature in biomedical literature
Authors:
Kafkas, Senay; Sarntivijai, Sirarat; Hoehndorf, Robert ( 0000-0001-8149-5890 )
Abstract:
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.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Kafkas Ş, Sarntivijai S, Hoehndorf R (2017) Usage of cell nomenclature in biomedical literature. BMC Bioinformatics 18. Available: http://dx.doi.org/10.1186/s12859-017-1978-0.
Publisher:
Springer Nature
Journal:
BMC Bioinformatics
Issue Date:
21-Dec-2017
DOI:
10.1186/s12859-017-1978-0
Type:
Article
ISSN:
1471-2105
Sponsors:
This work is supported by Wellcome Trust 108,437/Z/15/Z for Single Cell Expression Atlas, and the Chan Zuckerberg Initiative (CZI) for support of the Data Coordination Platform of the Human Cell Atlas. The funding body didn’t have any role in the design or conclusions of this study. Publication cost of this study was supported by funding from King Abdullah University of Science and Technology (KAUST).
Additional Links:
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1978-0
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKafkas, Senayen
dc.contributor.authorSarntivijai, Siraraten
dc.contributor.authorHoehndorf, Roberten
dc.date.accessioned2017-12-27T13:11:16Z-
dc.date.available2017-12-27T13:11:16Z-
dc.date.issued2017-12-21en
dc.identifier.citationKafkas Ş, Sarntivijai S, Hoehndorf R (2017) Usage of cell nomenclature in biomedical literature. BMC Bioinformatics 18. Available: http://dx.doi.org/10.1186/s12859-017-1978-0.en
dc.identifier.issn1471-2105en
dc.identifier.doi10.1186/s12859-017-1978-0en
dc.identifier.urihttp://hdl.handle.net/10754/626451-
dc.description.abstractBackground 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.en
dc.description.sponsorshipThis work is supported by Wellcome Trust 108,437/Z/15/Z for Single Cell Expression Atlas, and the Chan Zuckerberg Initiative (CZI) for support of the Data Coordination Platform of the Human Cell Atlas. The funding body didn’t have any role in the design or conclusions of this study. Publication cost of this study was supported by funding from King Abdullah University of Science and Technology (KAUST).en
dc.publisherSpringer Natureen
dc.relation.urlhttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1978-0en
dc.rightsThis 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.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectCell nomenclatureen
dc.subjectText miningen
dc.subjectCell linesen
dc.subjectCell typesen
dc.subjectOntologiesen
dc.titleUsage of cell nomenclature in biomedical literatureen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalBMC Bioinformaticsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionThe European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, SD CB10 1, UK.en
kaust.authorKafkas, Senayen
kaust.authorHoehndorf, Roberten
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