Title

Authors

Affiliation

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

sigven@ifi.uio.no; *Corresponding author

Article Type

Database

Date

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.

Availability

http://dev.pubgene.com/cellmine

Citation

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

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

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.