Abstract
We give an overview of our approach to the extraction of interactions between pharmacogenomic entities like drugs, genes and diseases and suggest classes of interaction types driven by data from PharmGKB and partly following the top level ontology WordNet and biomedical types from BioNLP. Our text mining approach to the extraction of interactions is based on syntactic analysis. We use syntactic analyses to explore domain events and to suggest a set of interaction labels for the pharmacogenomics domain.- Anthology ID:
- L12-1626
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 2075–2082
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/1052_Paper.pdf
- DOI:
- Cite (ACL):
- Gerold Schneider, Fabio Rinaldi, and Simon Clematide. 2012. Dependency parsing for interaction detection in pharmacogenomics. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 2075–2082, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- Dependency parsing for interaction detection in pharmacogenomics (Schneider et al., LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/1052_Paper.pdf