How to cite us

If you find iTextMine useful, please consider citing our publication:

Jia Ren, Gang Li, Karen Ross, Cecilia Arighi, Peter McGarvey, Shruti Rao, Julie Cowart, Subha Madhavan, K Vijay-Shanker, Cathy H Wu; iTextMine: integrated text-mining system for large-scale knowledge extraction from the literature, Database, Volume 2018, 1 January 2018, bay128, https://doi.org/10.1093/database/bay128

Citations of the underlying sources

iTextMine currently consists of four in-house developed text-mining tools: (i) RLIMS-P for mining protein phosphorylation (kinase substrate site), (ii) eFIP for phosphorylation-dependent protein–protein interaction (PPI), (iii) miRTex for miRNA–gene relation and (iv) eGARD for gene/protein variant therapeutic response in cancer information from the scientific literature. For gene and other entity normalization, we incorporated results from PubTator.

  • RLIMS-P: mining protein phosphorylation (kinase-substrate-site)
  • eFIP: phosphorylation-dependent protein-protein interactions (PPIs)
  • miRTex: miRNA-gene relations
  • eGARD: targeted therapy information from the scientific literature
  • PubTator: entity normalization