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CellLineMiner: a knowledge portal for human cell lines



Sigve Nakken1*, Morten Johansen1, Julien Fillebeen2, Ole Petter Berge2, Harald Kirkerød2, Tor-Kristian Jenssen2 & Eivind Hovig1,3,4



1Department of Tumor Biology, Institute for Cancer Research, Norwegian Radium Hospital - Oslo University Hospital, Norway; 2PubGene AS, Oslo, Norway; 3Department of Informatics, University of Oslo, Norway; 4Institute for Medical Informatics, Oslo University Hospital, Norway.


Email; *Corresponding author


Article Type



Received October 22, 2012; Accepted October 26, 2012; Published November 13, 2012



Experimental models of human tissues and disease phenotypes frequently rely upon immortalized cell lines, which are easily accessible and simple to use due to their infinite capability of cell division. For decades, cell lines have been used to investigate cellular mechanisms of disease and the efficacy of drugs, most prominently for human cancers. However, the large body of knowledge with respect to human cell lines exists primarily in an unstructured fashion, that is, as free text in the scientific literature. Here we present CellLineMiner, a novel text mining-based web database that provides a comprehensive view of human cell line knowledge. The application offers a simple search in all indexed cell lines, accompanied by a rapid display of all identified literature associations. The CellLineMiner is intended to serve as a knowledge resource companion to the cellular model systems used in biomedical research.





Nakken et al. Bioinformation 8(22): 1119-1122 (2012)

Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.