Abstract
AbstractLactoferrin is a metal-binding glycoprotein found in milk, blood and other exocrine secretions. This is a multi-functional protein that exhibits many activities such as: anti-microbial, anti-viral, immunomodulatory, anti-inflammatory, anti-tumor, anti-metastatic, cell growth-promoting, and anti-oxidant activities, as well as regulation of granulopoiesis and iron absorption, etc. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public databases. In order to overcome the information overload associated with lactoferrin information, we have applied the text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo), which uses natural language processing and text mining technology. Using GENPAC, text extraction was carried out on literature containing the term “lactoferrin” and any of keywords concerning health conditions or diseases from PubMed. Subsequently, network mappings of the information obtained were produced using Cytoscape. We will exhibit that such textmining method and information visualization analysis is useful in studying novel relationships among a multitude of lactoferrin functions and mechanisms to improve our health.
Highlights
A number of academic reports concerning the biological activities of lactoferrin have been published and are accessible through public databases
In order to overcome the information overload associated with lactoferrin information, we have applied the text mining method to the accumulated lactoferrin literature
We show three examples of lactoferrin’s functional pathways estimated by the textmining method
Summary
A number of academic reports concerning the biological activities of lactoferrin have been published and are accessible through public databases. In order to overcome the information overload associated with lactoferrin information, we have applied the text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo), which uses natural language processing and text mining technology. Using GENPAC, text extraction was carried out on literature containing the term "lactoferrin" and any of keywords concerning health conditions or diseases from PubMed. Subsequently, network mappings of the information obtained were produced using Cytoscape. Network mappings of the information obtained were produced using Cytoscape In this poster, we show three examples of lactoferrin’s functional pathways estimated by the textmining method. They are “lactoferrin and angiogenesis pathways”, “possible participation of lactoferrin against H. pylori’s attack” and “possible participations of lactoferrin and flavonoid against atopic dermatitis”
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