MET network in PubMed: a text-mined network visualization and curation system

Hong Jie Dai, Chu Hsien Su, Po Ting Lai, Ming Siang Huang, Jitendra Jonnagaddala, Toni Rose Jue, Shruti Rao, Hui Jou Chou, Marija Milacic, Onkar Singh, Shabbir Syed-Abdul, Wen Lian Hsu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL:

Original languageEnglish
JournalDatabase : the journal of biological databases and curation
Publication statusPublished - 2016

ASJC Scopus subject areas

  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)


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