Abstract
Genetic information in the literature has been extensively looked into for the purpose of discovering the etiology of a disease. As the gene-disease relation is sensitive to external factors, their identification is important to study a disease. Environmental influences, which are usually called Gene-Environment interaction (GxE), have been considered as important factors and have extensively been researched in biology. Nevertheless, there is still a lack of systems for automatic GxE extraction from the biomedical literature due to new challenges: (1) there are no preprocessing tools and corpora for GxE, (2) expressions of GxE are often quite implicit, and (3) document-level comprehension is usually required. We propose to overcome these challenges with neural network models and show that a modified sequence-to-sequence model with a static RNN decoder produces a good performance in GxE recognition.- Anthology ID:
- I17-1087
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Greg Kondrak, Taro Watanabe
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 865–874
- Language:
- URL:
- https://aclanthology.org/I17-1087
- DOI:
- Cite (ACL):
- Jinseon You, Jin-Woo Chung, Wonsuk Yang, and Jong C. Park. 2017. Extraction of Gene-Environment Interaction from the Biomedical Literature. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 865–874, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Extraction of Gene-Environment Interaction from the Biomedical Literature (You et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/I17-1087.pdf
- Data
- WikiReading