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

Hong-Jie Dai1, Chu-Hsien Su2, Po-Ting Lai3

  • 1Department of Computer Science and Information Engineering, National Taitung University, Taiwan, R.O.C Interdisciplinary Program of Green and Information Technology, National Taitung University, Taiwan R.O.C. hjdai@nttu.edu.tw.

Database : the Journal of Biological Databases and Curation
|June 1, 2016
PubMed

Insights

Researchers developed a METastasis (MET) network tool to visualize cancer metastasis pathways from PubMed literature. This tool aids in understanding complex cellular mechanisms and identifying key relations for improved cancer research.

Area of Science:

  • Oncology
  • Bioinformatics
  • Computational Biology

Background:

  • Metastasis, the spread of cancer, is responsible for over 90% of cancer-related deaths.
  • Understanding the complex cellular mechanisms of metastasis requires in-depth analysis of signaling pathways.
  • Existing literature in PubMed contains vast amounts of information on metastasis, necessitating efficient retrieval tools.

Purpose of the Study:

  • To develop a network visualization and curation tool (MET) for metastasis research.
  • To assist researchers in retrieving and understanding metastasis-related network information from PubMed.
  • To facilitate the curation of metastatic networks from scientific literature.

Main Methods:

  • Developed the METastasis (MET) network tool as a browser extension.
  • Utilized text-mining techniques to identify relations among genes, cancers, tissues, and organs in PubMed abstracts.
  • Integrated network visualization capabilities for direct viewing within PubMed.

Main Results:

  • Successfully curated 963 unique metastatic relations from 174 PubMed abstracts during the BioCreative 2015 interactive track.
  • Demonstrated the tool's utility for both researchers browsing PubMed and curators editing network data.
  • Enabled visualization of metastasis networks directly within the PubMed interface.

Conclusions:

  • The MET tool effectively aids in retrieving and visualizing metastasis-related network information from scientific literature.
  • Facilitates a deeper understanding of the complex cellular mechanisms underlying cancer metastasis.
  • Enhances the curation process for metastasis research, improving data accessibility and analysis.

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