Dynamical network biomarkers: Theory and applications

被引：39
|
作者：
Aihara, Kazuyuki [1 ]
Liu, Rui [2 ,3 ]
Koizumi, Keiichi [4 ,5 ]
Liu, Xiaoping [6 ,7 ]
Chen, Luonan [6 ,7 ,8 ,9 ]
机构：
[1] Univ Tokyo, Int Res Ctr Neurointelligence WPI IRCN, Bunkyo Ku, Tokyo 1130033, Japan
[2] South China Univ Technol, Sch Math, Guangzhou 510640, Peoples R China
[3] Pazhou Lab, Guangzhou 510330, Peoples R China
[4] Univ Toyama, Inst Nat Med, Div Kampo Diagnost, Toyama, Japan
[5] Univ Toyama, Inst Nat Med, Div Biosci, Sect Host Def,Lab Drug Discovery & Dev Predis, Toyama, Japan
[6] Chinese Acad Sci, Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Key Lab Syst Biol, Hangzhou 310024, Peoples R China
[7] Chinese Acad Sci, Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Key Lab Syst Hlth Sci Zhejiang Prov, Hangzhou 310024, Peoples R China
[8] Chinese Acad Sci, Ctr Excellence Mol Cell Sci, Shanghai Inst Biochem & Cell Biol, State Key Lab Cell Biol, Shanghai 200031, Peoples R China
[9] Chinese Acad Sci, Ctr Excellence Anim Evolut & Genet, Kunming 650223, Yunnan, Peoples R China
来源：
GENE | 2022年 / 808卷
关键词：
Dynamical network biomarker; Healthy state; Pre-disease state; Disease state; Bifurcation; Tipping point; Early warning signals; Ultra-early medicine; EARLY-WARNING SIGNALS; TIPPING POINT; TRANSITION; OBESITY; MODELS; MOUSE; STATE;
D O I：
10.1016/j.gene.2021.145997
中图分类号：
Q3 [遗传学];
学科分类号：
071007 ; 090102 ;
摘要：
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.
引用
收藏
页数：10
相关论文
共 50 条
  • [1] Early Diagnosis of Complex Diseases by Molecular Biomarkers, Network Biomarkers, and Dynamical Network Biomarkers
    Liu, Rui
    Wang, Xiangdong
    Aihara, Kazuyuki
    Chen, Luonan
    MEDICINAL RESEARCH REVIEWS, 2014, 34 (03) : 455 - 478
  • [2] Application of the Dynamical Network Biomarker Theory to Raman Spectra
    Haruki, Takayuki
    Yonezawa, Shota
    Koizumi, Keiichi
    Yoshida, Yasuhiko
    Watanabe, Tomonobu M.
    Fujita, Hideaki
    Oshima, Yusuke
    Oku, Makito
    Taketani, Akinori
    Yamazaki, Moe
    Ichimura, Taro
    Kadowaki, Makoto
    Kitajima, Isao
    Saito, Shigeru
    BIOMOLECULES, 2022, 12 (12)
  • [3] Understanding migraine using dynamic network biomarkers
    Dahlem, Markus A.
    Kurths, Juergen
    Ferrari, Michel D.
    Aihara, Kazuyuki
    Scheffer, Marten
    May, Arne
    CEPHALALGIA, 2015, 35 (07) : 627 - 630
  • [4] Economic Circuit Theory: Electrical Network Theory for Dynamical Economic Systems
    Hutters, Coen
    Mendel, Max B.
    IEEE ACCESS, 2024, 12 : 172696 - 172713
  • [5] Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers
    Sa, Rina
    Zhang, Wanwei
    Ge, Jing
    Wei, Xinben
    Zhou, Yunhua
    Landzberg, David R.
    Wang, Zhenzhen
    Han, Xianlin
    Chen, Luonan
    Yin, Huiyong
    JOURNAL OF MOLECULAR CELL BIOLOGY, 2016, 8 (03) : 195 - 206
  • [6] Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers
    Chen, Pei
    Liu, Rui
    Chen, Luonan
    Aihara, Kazuyuki
    FRONTIERS IN GENETICS, 2015, 6
  • [7] On global bifurcation theory of polynomial dynamical systems and its applications
    Gaiko, VA
    COMMUNICATIONS IN DIFFERENCE EQUATIONS, 2000, : 135 - 147
  • [8] Hunt for the tipping point during endocrine resistance process in breast cancer by dynamic network biomarkers
    Liu, Rui
    Wang, Jinzeng
    Ukai, Masao
    Sewon, Ki
    Chen, Pei
    Suzuki, Yutaka
    Wang, Haiyun
    Aihara, Kazuyuki
    Okada-Hatakeyama, Mariko
    Chen, Luonan
    JOURNAL OF MOLECULAR CELL BIOLOGY, 2019, 11 (08) : 649 - 664
  • [9] Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers
    Koizumi, Keiichi
    Oku, Makito
    Hayashi, Shusaku
    Inujima, Akiko
    Shibahara, Naotoshi
    Chen, Luonan
    Igarashi, Yoshiko
    Tobe, Kazuyuki
    Saito, Shigeru
    Kadowaki, Makoto
    Aihara, Kazuyuki
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [10] Detecting Early Warning Signal of Influenza A Disease Using Sample-Specific Dynamical Network Biomarkers
    Zhu, Shanshan
    Gao, Jie
    Ding, Tao
    Xu, Junhua
    Wu, Min
    BIOMED RESEARCH INTERNATIONAL, 2018, 2018
12345