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Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Updated: Oct 17, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Dynamical network biomarkers: Theory and applications.

Kazuyuki Aihara¹, Rui Liu², Keiichi Koizumi³

¹International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.

|October 9, 2021

Summary

This summary is machine-generated.

Dynamical Network Biomarkers (DNB) theory uses omics data to detect pre-disease states. This approach enables ultra-early precision and preventive medicine by identifying critical transitions before disease onset.

Keywords:

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

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Last Updated: Oct 17, 2025

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Area of Science:

Biomedical Science
Systems Biology
Computational Biology

Background:

Early disease detection remains a challenge in modern and traditional medicine.
Identifying pre-disease states is crucial for effective intervention.
Omics data offers a rich source of information for biological system analysis.

Purpose of the Study:

To review the theory of Dynamical Network Biomarkers (DNB).
To explore the applications of DNB theory in medicine.
To demonstrate the utility of DNB for detecting pre-disease states.

Main Methods:

Review of existing literature on DNB theory.
Analysis of omics data (gene/protein expression profiles).
Application of DNB theory to identify critical transitions in biological systems.

Main Results:

DNB theory provides a framework for understanding system dynamics.
Omics data can be effectively utilized to detect pre-disease states.
Early detection of critical transitions from healthy to disease states is feasible.

Conclusions:

DNB theory is applicable to both modern and traditional medicine.
The integration of DNB theory with big biological data facilitates ultra-early precision medicine.
This approach holds significant promise for preventive medicine.