New approach to generating insights for aging research based on literature mining and knowledge integration

Abstract

The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from. We demonstrate that our approach provides useful information that deepens insights on future trends which differs from data obtained conventionally, and this methodology is already paving the way for a new field in aging-related research based on literature mining. One compelling example of this is how our new approach can be a useful tool in drug repositioning.

[Retracted] An Evaluation Model for the Influence Factors of Interest in Literature Courses Based on Data Analysis and Association Rules in a Small‐Sample Environment

“…The latter is to distinguish the feature sets of data sets in the same subspace and different subspaces, so as to achieve effective data mining results. [23]. In junior high school, language and literature are equally important.…”

A novel method of literature mining to identify candidate COVID-19 drugs

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