Discovering breast cancer drug candidates from biomedical literature
by Jiao Li, Xiaoyan Zhu, Jake Yue Chen
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 4, No. 3, 2010

Abstract: We developed a new paradigm with the ultimate goal of enabling disease-specific drug candidate discovery with molecular-level evidences generated from literature and prior knowledge. We showed how to implement the paradigm by building a prototype literature-mining framework and performing drug–protein association mining for breast cancer drug discovery. In a molecular pharmacology study of breast cancer, 79.2% of 729 enriched drugs in 'Organic Chemicals' category were validated to be disease-related, and the remaining 20.8% were also investigated as potential for future molecular therapeutics studies. 'Doxorubicin', 'Etoposide' and 'Paclitaxel' were identified as having similar pharmacological profiles to treat breast cancer.

Online publication date: Wed, 02-Jun-2010

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