Literature-based discovery by lexical statistics
Journal of the American Society for Information Science
Journal of the American Society for Information Science and Technology
Using statistical and knowledge-based approaches for literature-based discovery
Journal of Biomedical Informatics
Literature mining method RaJoLink for uncovering relations between biomedical concepts
Journal of Biomedical Informatics
A new evaluation methodology for literature-based discovery systems
Journal of Biomedical Informatics
Recent research for MEDLINE/PubMed: short review
DTMBIO '10 Proceedings of the ACM fourth international workshop on Data and text mining in 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
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The biomedical literature is an important source of information about the biological activity and effects of chemicals. We present an application that extracts terms indicating biological activity of chemicals from Medline records, associates them with chemical name and stores the terms in a repository called ChemoText. We describe the construction of ChemoText and then demonstrate its utility in drug research by employing Swanson's ABC discovery paradigm. We reproduce Swanson's discovery of a connection between magnesium and migraine in a novel approach that uses only proteins as the intermediate B terms. We validate our methods by using a cutoff date and evaluate them by calculating precision and recall. In addition to magnesium, we have identified valproic acid and nitric oxide as chemicals which developed links to migraine. We hypothesize, based on protein annotations, that zinc and retinoic acid may play a role in migraine. The ChemoText repository has promise as a data source for drug discovery.