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Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses
BACKGROUND: Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is...
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/PMC5763302/ https://www.ncbi.nlm.nih.gov/pubmed/29322930 http://dx.doi.org/10.1186/s12859-017-1981-5 |
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author | Ong, Edison Xie, Jiangan Ni, Zhaohui Liu, Qingping Sarntivijai, Sirarat Lin, Yu Cooper, Daniel Terryn, Raymond Stathias, Vasileios Chung, Caty Schürer, Stephan He, Yongqun |
author_facet | Ong, Edison Xie, Jiangan Ni, Zhaohui Liu, Qingping Sarntivijai, Sirarat Lin, Yu Cooper, Daniel Terryn, Raymond Stathias, Vasileios Chung, Caty Schürer, Stephan He, Yongqun |
author_sort | Ong, Edison |
collection | PubMed |
description | BACKGROUND: Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration. RESULTS: CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL. Using MCF 10A cell line cells as an example, we demonstrated how to ontologically model LINCS cellular signatures such as their non-tumorigenic epithelial cell type, three-dimensional growth, latrunculin-A-induced actin depolymerization and apoptosis, and cell line transfection. A CLO subset view of LINCS cell lines, named LINCS-CLOview, was generated to support systematic LINCS cell line analysis and queries. In summary, LINCS cell lines are currently associated with 43 cell types, 131 tissues and organs, and 121 cancer types. The LINCS-CLO view information can be queried using SPARQL scripts. CONCLUSIONS: CLO was used to support ontological representation, integration, and analysis of over a thousand LINCS cell line cells and their cellular responses. |
format | Online Article Text |
id | pubmed-5763302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57633022018-01-17 Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses Ong, Edison Xie, Jiangan Ni, Zhaohui Liu, Qingping Sarntivijai, Sirarat Lin, Yu Cooper, Daniel Terryn, Raymond Stathias, Vasileios Chung, Caty Schürer, Stephan He, Yongqun BMC Bioinformatics Research BACKGROUND: Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration. RESULTS: CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL. Using MCF 10A cell line cells as an example, we demonstrated how to ontologically model LINCS cellular signatures such as their non-tumorigenic epithelial cell type, three-dimensional growth, latrunculin-A-induced actin depolymerization and apoptosis, and cell line transfection. A CLO subset view of LINCS cell lines, named LINCS-CLOview, was generated to support systematic LINCS cell line analysis and queries. In summary, LINCS cell lines are currently associated with 43 cell types, 131 tissues and organs, and 121 cancer types. The LINCS-CLO view information can be queried using SPARQL scripts. CONCLUSIONS: CLO was used to support ontological representation, integration, and analysis of over a thousand LINCS cell line cells and their cellular responses. BioMed Central 2017-12-21 /pmc/articles/PMC5763302/ /pubmed/29322930 http://dx.doi.org/10.1186/s12859-017-1981-5 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 Ong, Edison Xie, Jiangan Ni, Zhaohui Liu, Qingping Sarntivijai, Sirarat Lin, Yu Cooper, Daniel Terryn, Raymond Stathias, Vasileios Chung, Caty Schürer, Stephan He, Yongqun Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title | Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title_full | Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title_fullStr | Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title_full_unstemmed | Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title_short | Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses |
title_sort | ontological representation, integration, and analysis of lincs cell line cells and their cellular responses |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763302/ https://www.ncbi.nlm.nih.gov/pubmed/29322930 http://dx.doi.org/10.1186/s12859-017-1981-5 |
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