@InProceedings{you-EtAl:2017:I17-1,
  author    = {You, Jinseon  and  Chung, Jin-Woo  and  Yang, Wonsuk  and  Park, Jong C.},
  title     = {Extraction of Gene-Environment Interaction from the Biomedical Literature},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {865--874},
  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.},
  url       = {http://www.aclweb.org/anthology/I17-1087}
}