Recent progress in automatically extracting information from the pharmacogenomic literature. - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Pharmacogenomics / Personalized Medicine Year : 2010

Recent progress in automatically extracting information from the pharmacogenomic literature.

Yael Garten
  • Function : Author
Russ B Altman
  • Function : Author

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 extraction of specific types of information and can also provide answers to general, systemic queries. In this article, we describe the main tasks of text mining in the context of pharmacogenomics, summarize recent applications and anticipate the next phase of text mining applications.

Dates and versions

inria-00549699 , version 1 (22-12-2010)

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Yael Garten, Adrien Coulet, Russ B Altman. Recent progress in automatically extracting information from the pharmacogenomic literature.. Pharmacogenomics / Personalized Medicine, 2010, 11 (10), pp.1467-89. ⟨10.2217/pgs.10.136⟩. ⟨inria-00549699⟩
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