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

Edison Ong, Jiangan Xie, Zhaohui Ni, Qingping Liu, Sirarat Sarntivijai, Yu Lin, Daniel Cooper, Raymond Terryn, Vasileios Stathias, Caty Chung, Stephan Schürer, Yongqun He

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Article number556
JournalBMC Bioinformatics
StatePublished - Dec 21 2017


  • Cell line
  • Cell line ontology
  • ChEMBL
  • Data integration
  • Lincs
  • Ontology

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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