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Updated: Jun 15, 2026
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.
Kei-ichi Shimazaki1, Tatsuya Kushida
1Hokkaido University, Sapporo, Japan. simazaki@anim.agr.hokudai.ac.jp
Summary
Text mining of lactoferrin literature reveals novel biological functions and mechanisms. This approach helps researchers navigate the expanding body of knowledge on this important glycoprotein.
Area of Science:
- Biochemistry
- Bioinformatics
- Molecular Biology
Background:
- Lactoferrin is a versatile glycoprotein with diverse biological roles.
- The rapid growth of lactoferrin research presents challenges in synthesizing information.
- Existing literature repositories offer vast but complex data on lactoferrin.
Purpose of the Study:
- To apply text mining for a comprehensive understanding of lactoferrin functions.
- To identify novel relationships between lactoferrin, its mechanisms, and biological processes.
- To overcome information overload in lactoferrin research.
Main Methods:
- Utilized the GENPAC information extraction system.
- Employed natural language processing and text mining on PubMed abstracts.
- Extracted binary relations between genes/proteins, chemicals, and diseases/functions.
Main Results:
- Demonstrated text mining for pathway discovery in lactoferrin research.
- Identified lactoferrin's role in neovascularization.
- Revealed connections to Helicobacter pylori infection, atopic dermatitis, and lipid metabolism.
Conclusions:
- Text mining provides a powerful tool for analyzing complex biological literature.
- This method facilitates the discovery of new insights into lactoferrin's multifaceted activities.
- Information visualization aids in understanding intricate biological pathways.
