Recent progress in automatically extracting information from the pharmacogenomic literature.

ABSTRACT: The biomedical literature holds our understanding of pharmacogenomics, but it is dispersed across many journals. In order to integrate our knowledge, connect important facts across publications and generate new hypotheses we must organize and encode the contents of the literature. By creating databases of structured pharmocogenomic knowledge, we can make the value of the literature much greater than the sum of the individual reports. We can, for example, generate candidate gene lists or interpret surprising hits in genome-wide association studies. Text mining automatically adds structure to the unstructured knowledge embedded in millions of publications, and recent years have seen a surge in work on biomedical text mining, some specific to pharmacogenomics literature. These methods enable

SUBMITTER: Garten Y 

PROVIDER: S-EPMC3035632 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature