Abstract
We present an interactive discovery support system, which for a given starting concept of interest, discovers new, potentially meaningful relations with other concepts that have not been published in the medical literature before. The known relations between the medical concepts come from the MEDLINE bibliographic database and the UMLS (Unified Medical Language System). We use association rules to mine for the relationships between medical concepts. Then we demonstrate a successful application of the system for predicting a gene candidate for a disease, a fact recently confirmed via the positional cloning approach. We conclude that the discovery support system we developed is a useful tool, complementary to the already existing bioinformatic tools in the field of human genetics. The system described in this chapter is available at http://www.mf.uni-lj.si/bitola/
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Hristovski, D., Peterlin, B., Džeroski, S., Stare, J. (2007). Literature Based Discovery Support System and Its Application to Disease Gene Identification. In: Džeroski, S., Todorovski, L. (eds) Computational Discovery of Scientific Knowledge. Lecture Notes in Computer Science(), vol 4660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73920-3_15
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DOI: https://doi.org/10.1007/978-3-540-73920-3_15
Publisher Name: Springer, Berlin, Heidelberg
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