Evidence map›Paper›PMID 31272367›Full record

ArticleBMC bioinformatics2019

The cell line ontology-based representation, integration and analysis of cell lines used in China.

Hongjie Pan, Xiaocui Bian, Sheng Yang, Yongqun He, Xiaolin Yang, Yuqin Liu

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hongjie PanInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China.
Xiaocui BianInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China.
Sheng YangInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China.
Yongqun HeUniversity of Michigan Medical School, Ann Arbor, MI 48109, USA.
Xiaolin YangInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China. yangxl@pumc.edu.cn.
Yuqin LiuInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China. liuyuqin@pumc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Chinese National Infrastructure of Cell Line stores and distributes cell lines for biomedical research in China. This study aims to represent and integrate the information of NICR cell lines into the community-based Cell Line Ontology (CLO).

resultsWe have aligned, represented, and added all identified 2704 cell line cells in NICR to CLO. We also proposed new ontology design patterns to represent the usage of cell line cells as disease models by inducing tumor formation in model organisms, and the relations between cell line cells and their expressed or overexpressed genes or proteins. The resulting CLO-NICR ontology also includes the Chinese representation of the NICR cell line information. CLO-NICR was merged into the general CLO. To serve the cell research community in China, the Chinese version of CLO-NICR was also generated and deposited in the OntoChina ontology repository. The usage of CLO-NICR was demonstrated by DL query and knowledge extraction.

conclusionsIn summary, all identified cell lines from NICR are represented by the semantics framework of CLO and incorporated into CLO as a most recent update. We also generated a CLO-NICR and its Chinese view (CLO-NICR-Cv). The development of CLO-NICR and CLO-NIC-Cv allows the integration of the cell lines from NICR into the community-based CLO ontology and provides an integrative platform to support different applications of CLO in China.

Indexed as

Biological OntologiesUser-Computer InterfaceBiomedical ResearchCell LineChinaDatabases, FactualHumansCell line cellCell line ontologyData integrationOntology

Identifiers

PMID31272367
PMCPMC6509802

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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.