Toward an automatic method for extracting cancer- and other disease-related point mutations from the biomedical literature.

From the abstract: A major goal of biomedical research in personalized medicine is to find relationships between mutations and their corresponding disease phenotypes. However, most of the disease-related mutational data are currently buried in the biomedical literature in textual form and lack the necessary structure to allow easy retrieval and visualization. We introduce a high-throughput computational method for the identification of relevant disease mutations in Pub-Med abstracts applied to prostate (PCa) and breast cancer (BCa) mutations....We further show that our method can benefit from full text analysis once there is an increase in Open Access availability of full text articles.