Apply of Textmining Method to Study the Roles in Improving the Health by Lactoferrin, a Multi-Functional Milk Protein

摘要

Lactoferrin 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.