Identifying the critical state of cancers by single-sample Markov flow entropy
Background The progression of complex diseases sometimes undergoes a drastic critical transition, at which the biological system abruptly shifts from a relatively healthy state (before-transition stage) to a disease state (after-transition stage). Searching for such a critical transition or critical...
Main Authors: | Juntan Liu, Yuan Tao, Ruoqi Lan, Jiayuan Zhong, Rui Liu, Pei Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2023-07-01
|
Series: | PeerJ |
Subjects: | |
Online Access: | https://peerj.com/articles/15695.pdf |
Similar Items
-
Identifying the critical states and dynamic network biomarkers of cancers based on network entropy
by: Juntan Liu, et al.
Published: (2022-06-01) -
Identifying Critical State of Complex Diseases by Single-Sample-Based Hidden Markov Model
by: Rui Liu, et al.
Published: (2019-04-01) -
MIWE: detecting the critical states of complex biological systems by the mutual information weighted entropy
by: Yuke Xie, et al.
Published: (2024-01-01) -
Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers
by: Pei eChen, et al.
Published: (2015-07-01) -
Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence
by: Jinling Yan, et al.
Published: (2021-06-01)