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Evidence-Based Complementary and Alternative Medicine
Volume 2013 (2013), Article ID 235969, 9 pages
Review Article

ZHENG-Omics Application in ZHENG Classification and Treatment: Chinese Personalized Medicine

1Center for Traditional Chinese Medicine and Systems Biology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
2Department of Integrated Oncology, Shanghai Cancer Center, Fudan University, Shanghai 200032, China
3School of Chinese Medicine, Hong Kong Baptist University, Hong Kong

Received 10 January 2013; Revised 22 February 2013; Accepted 27 February 2013

Academic Editor: Zhaoxiang Bian

Copyright © 2013 Jianye Dai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the hope to provide an effective approach for personalized diagnosis and treatment clinically, traditional chinese medicine (TCM) is being paid increasing attention as a complementary and alternative medicine. It performs treatment based on ZHENG (TCM syndrome) classification, which could be identified clinical special phenotypes by symptoms and signs of patients even if they have a different disease. However, it caused controversy because ZHENG classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. Although researchers and scientists of TCM have done some work with a lot of beneficial methods, the results could not reach satisfactory with the shortcomings of generalizing the entire state of the body or ignoring the patients' feelings. By total summary, mining, and integration of existing researches, the present paper attempts to introduce a novel macro-microconcept of ZHENG-omics, with the prospect of bright future in providing an objective and repeatable approach for Chinese personalized medicine in an effective way. In this paper, we give the brief introduction and preliminary validation, and discuss strategies and system-oriented technologies for achieving this goal.