BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

124 related articles for article (PubMed ID: 35598334)

  • 1. Identifying the critical states of complex diseases by the dynamic change of multivariate distribution.
    Peng H; Zhong J; Chen P; Liu R
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35598334
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Identifying the critical state of complex biological systems by the directed-network rank score method.
    Zhong J; Han C; Wang Y; Chen P; Liu R
    Bioinformatics; 2022 Dec; 38(24):5398-5405. PubMed ID: 36282843
    [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. 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]  

  • 6. 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]  

  • 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. 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]  

  • 9. 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]  

  • 10. Development of a dynamic network biomarkers method and its application for detecting the tipping point of prior disease development.
    Han C; Zhong J; Zhang Q; Hu J; Liu R; Liu H; Mo Z; Chen P; Ling F
    Comput Struct Biotechnol J; 2022; 20():1189-1197. PubMed ID: 35317238
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage.
    Zhang C; Zhang H; Ge J; Mi T; Cui X; Tu F; Gu X; Zeng T; Chen L
    J Mol Cell Biol; 2022 Jan; 13(11):822-833. PubMed ID: 34609489
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genome-wide dynamic network analysis reveals a critical transition state of flower development in Arabidopsis.
    Zhang F; Liu X; Zhang A; Jiang Z; Chen L; Zhang X
    BMC Plant Biol; 2019 Jan; 19(1):11. PubMed ID: 30616516
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers.
    Lu L; Jiang Z; Dai Y; Chen L
    Genes (Basel); 2017 Oct; 8(10):. PubMed ID: 29027943
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identifying Critical State of Complex Diseases by Single-Sample-Based Hidden Markov Model.
    Liu R; Zhong J; Yu X; Li Y; Chen P
    Front Genet; 2019; 10():285. PubMed ID: 31019526
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers.
    Chen L; Liu R; Liu ZP; Li M; Aihara K
    Sci Rep; 2012; 2():342. PubMed ID: 22461973
    [TBL] [Abstract][Full Text] [Related]  

  • 20. SGAE: single-cell gene association entropy for revealing critical states of cell transitions during embryonic development.
    Zhong J; Han C; Chen P; Liu R
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37833841
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.