Edge-based relative entropy as a sensitive indicator of critical transitions in biological systems.

ABSTRACT:

Background

Disease progression in biosystems is not always a steady process but is occasionally abrupt. It is important but challenging to signal critical transitions in complex biosystems.

Methods

In this study, based on the theoretical framework of dynamic network biomarkers (DNBs), we propose a model-free method, edge-based relative entropy (ERE), to identify temporal key biomolecular associations/networks that may serve as DNBs and detect early-warning signals of the drastic state transition during disease progression in complex biological systems. Specifically, by combining gene‒gene interaction (edge) information with the relative entropy, the ERE method converts gene expression values into network entropy values, quantifying the dynamic change in a biomolecular networ

SUBMITTER: Hong R 

PROVIDER: S-EPMC10996174 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature