Knowledge discovery based on an implicit and explicit conceptual network
Journal of the American Society for Information Science and Technology
Biomedical knowledge navigation by literature clustering
Journal of Biomedical Informatics
Natural language processing and visualization in the molecular imaging domain
Journal of Biomedical Informatics
A new evaluation methodology for literature-based discovery systems
Journal of Biomedical Informatics
RaJoLink: A Method for Finding Seeds of Future Discoveries in Nowadays Literature
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Using annotations from controlled vocabularies to find meaningful associations
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
Discovering breast cancer drug candidates from biomedical literature
International Journal of Data Mining and Bioinformatics
Mining connections between chemicals, proteins, and diseases extracted from Medline annotations
Journal of Biomedical Informatics
A text-mining technique for extracting gene-disease associations from the biomedical literature
International Journal of Bioinformatics Research and Applications
Semi-automatic semantic annotation of PubMed queries: A study on quality, efficiency, satisfaction
Journal of Biomedical Informatics
Inferring hidden relationships from biological literature with multi-level context terms
Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics
Bisociative knowledge discovery by literature outlier detection
Bisociative Knowledge Discovery
Systematic identification of pharmacogenomics information from clinical trials
Journal of Biomedical Informatics
A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications
Journal of Biomedical Informatics
Leveraging concept-based approaches to identify potential phyto-therapies
Journal of Biomedical Informatics
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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.