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Sarntivijai S; Lin Y; Xiang Z; Meehan TF; Diehl AD; Vempati UD; Schürer SC; Pang C; Malone J; Parkinson H; Liu Y; Takatsuki T; Saijo K; Masuya H; Nakamura Y; Brush MH; Haendel MA; Zheng J; Stoeckert CJ; Peters B; Mungall CJ; Carey TE; States DJ; Athey BD; He Y
J Biomed Semantics 2014[]; 5 (ä): 37 PMID25852852show ga
Background: Cell lines have been widely used in biomedical research. The community-based Cell Line Ontology (CLO) is a member of the OBO Foundry library that covers the domain of cell lines. Since its publication two years ago, significant updates have been made, including new groups joining the CLO consortium, new cell line cells, upper level alignment with the Cell Ontology (CL) and the Ontology for Biomedical Investigation, and logical extensions. Construction and content: Collaboration among the CLO, CL, and OBI has established consensus definitions of cell line-specific terms such as ?cell line?, ?cell line cell?, ?cell line culturing?, and ?mortal? vs. ?immortal cell line cell?. A cell line is a genetically stable cultured cell population that contains individual cell line cells. The hierarchical structure of the CLO is built based on the hierarchy of the in vivo cell types defined in CL and tissue types (from which cell line cells are derived) defined in the UBERON cross-species anatomy ontology. The new hierarchical structure makes it easier to browse, query, and perform automated classification. We have recently added classes representing more than 2,000 cell line cells from the RIKEN BRC Cell Bank to CLO. Overall, the CLO now contains ~38,000 classes of specific cell line cells derived from over 200 in vivo cell types from various organisms. Utility and discussion: The CLO has been applied to different biomedical research studies. Example case studies include annotation and analysis of EBI ArrayExpress data, bioassays, and host-vaccine/pathogen interaction. CLO?s utility goes beyond a catalogue of cell line types. The alignment of the CLO with related ontologies combined with the use of ontological reasoners will support sophisticated inferencing to advance translational informatics development.
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J+Biomed+Semantics 2014 ; 5 (ä): 37
