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Bioinformatics 20(Suppl. 1) © Oxford University Press 2004; all rights reserved.

Mining MEDLINE for implicit links between dietary substances and diseases

Padmini Srinivasan 1,* and Bisharah Libbus 2

1 School of Library and Information Science, University of Iowa, Iowa City, IA 52242, USA and 2 Lister Hill Research Center, National Library of Medicine, Bethesda, MD 20852, USA

Received on January 15, 2004; accepted on March 1, 2004

Motivation: Text mining systems aim at knowledge discovery from text collections. This work presents our text mining algorithm and demonstrates its use to uncover information that could form the basis of new hypotheses. In particular, we use it to discover novel uses for Curcuma longa, a dietary substance, which is highly regarded for its therapeutic properties in Asia.

Results: Several disease were identified that offer novel research contexts for curcumin. We analyze select suggestions, such as retinal diseases, Crohn's disease and disorders related to the spinal cord. Our analysis suggests that there is strong evidence in favor of a beneficial role for curcumin in these diseases. The evidence is based on curcumin's influence on several genes, such as COX-2, TNF-alpha, JNK, p38 MAPK and TGF-beta. This research suggests that our discovery algorithm may be used to suggest novel uses for dietary and pharmacological substances. More generally, our text mining algorithm may be used to uncover information that potentially sheds new light on a given topic of interest.

Availability: Contact authors.

Contact: padmini-srinivasan{at}uiowa.edu

* To whom correspondence should be addressed.


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