Open Access Open Badges Methodology article

CELDA – an ontology for the comprehensive representation of cells in complex systems

Stefanie Seltmann1, Harald Stachelscheid1, Alexander Damaschun1, Ludger Jansen2, Fritz Lekschas1, Jean-Fred Fontaine6, Throng Nghia Nguyen-Dobinsky3, Ulf Leser5 and Andreas Kurtz14*

Author Affiliations

1 Charité-Universitätsmedizin Berlin, Berlin Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany

2 Institute of Philosophy, University of Rostock, Rostock, Germany

3 Charité-Universitätsmedizin Berlin, Medical Informatics and Bioinformatics, Berlin, Germany

4 College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, Republic of Korea

5 Humboldt Universität zu Berlin, Wissensmanagement in der Bioinformatik, Institut für Informatik, Berlin, Germany

6 Max Delbrück Center for Molecular Medicine, Berlin, Germany

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BMC Bioinformatics 2013, 14:228  doi:10.1186/1471-2105-14-228

Published: 17 July 2013



The need for detailed description and modeling of cells drives the continuous generation of large and diverse datasets. Unfortunately, there exists no systematic and comprehensive way to organize these datasets and their information. CELDA (Cell: Expression, Localization, Development, Anatomy) is a novel ontology for the association of primary experimental data and derived knowledge to various types of cells of organisms.


CELDA is a structure that can help to categorize cell types based on species, anatomical localization, subcellular structures, developmental stages and origin. It targets cells in vitro as well as in vivo. Instead of developing a novel ontology from scratch, we carefully designed CELDA in such a way that existing ontologies were integrated as much as possible, and only minimal extensions were performed to cover those classes and areas not present in any existing model. Currently, ten existing ontologies and models are linked to CELDA through the top-level ontology BioTop. Together with 15.439 newly created classes, CELDA contains more than 196.000 classes and 233.670 relationship axioms. CELDA is primarily used as a representational framework for modeling, analyzing and comparing cells within and across species in CellFinder, a web based data repository on cells ( webcite).


CELDA can semantically link diverse types of information about cell types. It has been integrated within the research platform CellFinder, where it exemplarily relates cell types from liver and kidney during development on the one hand and anatomical locations in humans on the other, integrating information on all spatial and temporal stages. CELDA is available from the CellFinder website: webcite.