Aihara Kazuyuki, Liu Rui, Koizumi Keiichi, Liu Xiaoping, Chen Luonan
International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
School of Mathematics, South China University of Technology, Guangzhou 510640, China; Pazhou Lab, Guangzhou 510330, China.
Gene. 2022 Jan 15;808:145997. doi: 10.1016/j.gene.2021.145997. Epub 2021 Oct 6.
This paper reviews theory of DNB (Dynamical Network Biomarkers) and its applications including both modern medicine and traditional medicine. We show that omics data such as gene/protein expression profiles can be effectively used to detect pre-disease states before critical transitions from healthy states to disease states by using the DNB theory. The DNB theory with big biological data is expected to lead to ultra-early precision and preventive medicine.
本文综述了动态网络生物标志物(DNB)理论及其在现代医学和传统医学中的应用。我们表明,通过使用DNB理论,基因/蛋白质表达谱等组学数据可有效地用于在从健康状态到疾病状态的关键转变之前检测疾病前状态。具有大量生物数据的DNB理论有望带来超早期精准预防医学。