Dynamical network biomarkers: Theory and applications

Kazuyuki Aihara; Rui Liu; Keiichi Koizumi; Xiaoping Liu; Luonan Chen

doi:10.1016/j.gene.2021.145997

Dynamical network biomarkers: Theory and applications

Kazuyuki Aihara^*, Rui Liu, Keiichi Koizumi, Xiaoping Liu, Luonan Chen

^*Corresponding author for this work

Presymptomatic Disease, Institute of Natural Medicine

Research output: Contribution to journal › Article › peer-review

44 Scopus citations

Abstract

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.

Original language	English
Article number	145997
Journal	Gene
Volume	808
DOIs	https://doi.org/10.1016/j.gene.2021.145997
State	Published - 2022/01/15

Keywords

Bifurcation
Disease state
Dynamical network biomarker
Early warning signals
Healthy state
Pre-disease state
Tipping point
Ultra-early medicine

ASJC Scopus subject areas

Genetics

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10.1016/j.gene.2021.145997

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title = "Dynamical network biomarkers: Theory and applications",

abstract = "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.",

keywords = "Bifurcation, Disease state, Dynamical network biomarker, Early warning signals, Healthy state, Pre-disease state, Tipping point, Ultra-early medicine",

author = "Kazuyuki Aihara and Rui Liu and Keiichi Koizumi and Xiaoping Liu and Luonan Chen",

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year = "2022",

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doi = "10.1016/j.gene.2021.145997",

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AU - Liu, Rui

AU - Koizumi, Keiichi

AU - Liu, Xiaoping

AU - Chen, Luonan

PY - 2022/1/15

Y1 - 2022/1/15

N2 - 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.

AB - 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.

KW - Bifurcation

KW - Disease state

KW - Dynamical network biomarker

KW - Early warning signals

KW - Healthy state

KW - Pre-disease state

KW - Tipping point

KW - Ultra-early medicine

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SN - 0378-1119

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JO - Gene

JF - Gene

M1 - 145997

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Dynamical network biomarkers: Theory and applications

Abstract

Keywords

ASJC Scopus subject areas

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