LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Deciphering Potential Correlations between New Biomarkers and Pattern Classification in Chinese Medicine by Bioinformatics: Two Examples of Rheumatoid Arthritis

Photo by bady from unsplash

Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging. Thus, new paradigms for research need to be created that bring together a different… Click to show full abstract

Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging. Thus, new paradigms for research need to be created that bring together a different classifier of individuals. One potential solution is collaboration between biomarker development and Chinese medicine pattern classification. In this article, two examples of rheumatoid arthritis are discussed, including a new biomarker candidate casein kinase 2 interacting protein 1 (CKIP-1) and a micro RNA 214. The authors obtained a “snapshot” of pattern classification with disease in biomarker identification. Bioinformatics analyses revealed underlying biological functions of two biomarker candidates, in varying degrees, are correlated with Chinese medicine pattern of rheumatoid arthritis. The authors’ initial attempt can provide a new window for studying the win-win potential correlation between the biomarkers and pattern classification in Chinese medicine.

Keywords: medicine; biomarker; pattern classification; chinese medicine; rheumatoid arthritis

Journal Title: Chinese Journal of Integrative Medicine
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.