175 related articles for article (PubMed ID: 35668489)
1. Identifying the critical states and dynamic network biomarkers of cancers based on network entropy.
Liu J; Ding D; Zhong J; Liu R
J Transl Med; 2022 Jun; 20(1):254. PubMed ID: 35668489
[TBL] [Abstract][Full Text] [Related]
2. Identifying the critical state of cancers by single-sample Markov flow entropy.
Liu J; Tao Y; Lan R; Zhong J; Liu R; Chen P
PeerJ; 2023; 11():e15695. PubMed ID: 37520244
[TBL] [Abstract][Full Text] [Related]
3. Edge-based relative entropy as a sensitive indicator of critical transitions in biological systems.
Hong R; Tong Y; Liu H; Chen P; Liu R
J Transl Med; 2024 Apr; 22(1):333. PubMed ID: 38576021
[TBL] [Abstract][Full Text] [Related]
4. SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems.
Zhong J; Ding D; Liu J; Liu R; Chen P
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36705581
[TBL] [Abstract][Full Text] [Related]
5. Detecting the critical states during disease development based on temporal network flow entropy.
Gao R; Yan J; Li P; Chen L
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35580862
[TBL] [Abstract][Full Text] [Related]
6. The single-sample network module biomarkers (sNMB) method reveals the pre-deterioration stage of disease progression.
Zhong J; Liu H; Chen P
J Mol Cell Biol; 2022 Dec; 14(8):. PubMed ID: 36069893
[TBL] [Abstract][Full Text] [Related]
7. Identifying critical state of complex diseases by single-sample Kullback-Leibler divergence.
Zhong J; Liu R; Chen P
BMC Genomics; 2020 Jan; 21(1):87. PubMed ID: 31992202
[TBL] [Abstract][Full Text] [Related]
8. mNFE: microbiome network flow entropy for detecting pre-disease states of type 1 diabetes.
Gao R; Li P; Ni Y; Peng X; Ren J; Chen L
Gut Microbes; 2024; 16(1):2327349. PubMed ID: 38512768
[TBL] [Abstract][Full Text] [Related]
9. Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence.
Yan J; Li P; Gao R; Li Y; Chen L
Front Oncol; 2021; 11():684781. PubMed ID: 34150649
[TBL] [Abstract][Full Text] [Related]
10. Detecting the Critical States of Type 2 Diabetes Mellitus Based on Degree Matrix Network Entropy by Cross-Tissue Analysis.
Yang Y; Tian Z; Song M; Ma C; Ge Z; Li P
Entropy (Basel); 2022 Sep; 24(9):. PubMed ID: 36141135
[TBL] [Abstract][Full Text] [Related]
11. MIWE: detecting the critical states of complex biological systems by the mutual information weighted entropy.
Xie Y; Peng X; Li P
BMC Bioinformatics; 2024 Jan; 25(1):44. PubMed ID: 38280998
[TBL] [Abstract][Full Text] [Related]
12. CPMI: comprehensive neighborhood-based perturbed mutual information for identifying critical states of complex biological processes.
Ren J; Li P; Yan J
BMC Bioinformatics; 2024 Jun; 25(1):215. PubMed ID: 38879513
[TBL] [Abstract][Full Text] [Related]
13. Detecting tissue-specific early warning signals for complex diseases based on dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis.
Li M; Zeng T; Liu R; Chen L
Brief Bioinform; 2014 Mar; 15(2):229-43. PubMed ID: 23620135
[TBL] [Abstract][Full Text] [Related]
14. Single-Sample Node Entropy for Molecular Transition in Pre-deterioration Stage of Cancer.
Han C; Zhong J; Hu J; Liu H; Liu R; Ling F
Front Bioeng Biotechnol; 2020; 8():809. PubMed ID: 32766227
[TBL] [Abstract][Full Text] [Related]
15. Detecting the tipping points in a three-state model of complex diseases by temporal differential networks.
Chen P; Li Y; Liu X; Liu R; Chen L
J Transl Med; 2017 Oct; 15(1):217. PubMed ID: 29073904
[TBL] [Abstract][Full Text] [Related]
16. Quantifying critical states of complex diseases using single-sample dynamic network biomarkers.
Liu X; Chang X; Liu R; Yu X; Chen L; Aihara K
PLoS Comput Biol; 2017 Jul; 13(7):e1005633. PubMed ID: 28678795
[TBL] [Abstract][Full Text] [Related]
17. TPD: a web tool for tipping-point detection based on dynamic network biomarker.
Chen P; Zhong J; Yang K; Zhang X; Chen Y; Liu R
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36088546
[TBL] [Abstract][Full Text] [Related]
18. Detection for disease tipping points by landscape dynamic network biomarkers.
Liu X; Chang X; Leng S; Tang H; Aihara K; Chen L
Natl Sci Rev; 2019 Jul; 6(4):775-785. PubMed ID: 34691933
[TBL] [Abstract][Full Text] [Related]
19. Uncovering the Pre-Deterioration State during Disease Progression Based on Sample-Specific Causality Network Entropy (SCNE).
Zhong J; Tang H; Huang Z; Chai H; Ling F; Chen P; Liu R
Research (Wash D C); 2024; 7():0368. PubMed ID: 38716473
[TBL] [Abstract][Full Text] [Related]
20. [Identifying critical state of breast cancer cell differentiation based on landscape dynamic network biomarkers].
Zhao H; Gao J
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2020 Apr; 37(2):304-310. PubMed ID: 32329283
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]