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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.
Afiliación
  • Ong E; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Xie J; Unit of Laboratory Animal Medicine and Department of Micro biology and Immunology, University of Michigan, Ann Arbor, MI, USA.
  • Ni Z; Unit of Laboratory Animal Medicine and Department of Micro biology and Immunology, University of Michigan, Ann Arbor, MI, USA.
  • Liu Q; Unit of Laboratory Animal Medicine and Department of Micro biology and Immunology, University of Michigan, Ann Arbor, MI, USA.
  • Sarntivijai S; Samples, Phenotypes and Ontologies Team, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Hinxton, Cambridge, UK.
  • Lin Y; Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL, USA.
  • Cooper D; Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL, USA.
  • Terryn R; BD2K LINCS Data Coordination and Integration Center, University of Miami, Miami, FL, USA.
  • Stathias V; Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL, USA.
  • Chung C; BD2K LINCS Data Coordination and Integration Center, University of Miami, Miami, FL, USA.
  • Schürer S; Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL, USA.
  • He Y; BD2K LINCS Data Coordination and Integration Center, University of Miami, Miami, FL, USA.
BMC Bioinformatics ; 18(Suppl 17): 556, 2017 12 21.
Article en En | MEDLINE | ID: mdl-29322930
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Mama / Regulación de la Expresión Génica / Biología Computacional / Ensayos Analíticos de Alto Rendimiento / Neoplasias Límite: Female / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Mama / Regulación de la Expresión Génica / Biología Computacional / Ensayos Analíticos de Alto Rendimiento / Neoplasias Límite: Female / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos