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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
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PubMed
Summary

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.

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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.