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Updated: Oct 7, 2025
07:35
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
1.8K
NETME: on-the-fly knowledge network construction from biomedical literature.
Alessandro Muscolino1, Antonio Di Maria2, Rosaria Valentina Rapicavoli1
1Department of Physics and Astronomy, University of Catania, Catania, Italy.
Applied Network Science
|January 11, 2022
Summary
We developed NETME, a novel system that extracts biological elements and infers relationships from PubMed full-texts to build comprehensive knowledge networks for biological discovery.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Biological literature is rapidly expanding, necessitating automated knowledge extraction.
- Knowledge Networks are crucial for biological knowledge discovery and modeling.
Purpose of the Study:
- To introduce NETME, a novel system for interactive biological knowledge network synthesis.
- To facilitate the extraction of biological elements and inference of their relationships from scientific literature.
Main Methods:
- NETME processes full-text articles from PubMed via a web interface.
- It interactively extracts biological elements using ontological databases.
- The system synthesizes these elements into a network, inferring relationships.
Main Results:
- NETME successfully infers comprehensive and reliable biological networks.
- The system demonstrates the capability to handle large volumes of biological literature.
Conclusions:
- NETME provides an effective tool for biological knowledge discovery.
- The system aids in modeling complex biological relationships from text data.
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