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Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses

Authors :
Edison Ong
Jiangan Xie
Zhaohui Ni
Qingping Liu
Sirarat Sarntivijai
Yu Lin
Daniel Cooper
Raymond Terryn
Vasileios Stathias
Caty Chung
Stephan Schürer
Yongqun He
Source :
BMC Bioinformatics, Vol 18, Iss S17, Pp 43-53 (2017)
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14712105
Volume :
18
Issue :
S17
Database :
Directory of Open Access Journals
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.0d2ffb7e1a624ac4bc3f83d3763c86a3
Document Type :
article
Full Text :
https://doi.org/10.1186/s12859-017-1981-5