These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

189 related articles for article (PubMed ID: 34560840)

  • 1. Identification of driver genes based on gene mutational effects and network centrality.
    Tang YY; Wei PJ; Zhao JP; Xia J; Cao RF; Zheng CH
    BMC Bioinformatics; 2021 Sep; 22(Suppl 3):457. PubMed ID: 34560840
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes.
    Dopazo J; Erten C
    BMC Syst Biol; 2017 Nov; 11(1):110. PubMed ID: 29166896
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identifying overlapping mutated driver pathways by constructing gene networks in cancer.
    Wu H; Gao L; Li F; Song F; Yang X; Kasabov N
    BMC Bioinformatics; 2015; 16 Suppl 5(Suppl 5):S3. PubMed ID: 25859819
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A novel network control model for identifying personalized driver genes in cancer.
    Guo WF; Zhang SW; Zeng T; Li Y; Gao J; Chen L
    PLoS Comput Biol; 2019 Nov; 15(11):e1007520. PubMed ID: 31765387
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cancer Gene Discovery by Network Analysis of Somatic Mutations Using the MUFFINN Server.
    Han H; Lehner B; Lee I
    Methods Mol Biol; 2019; 1907():37-50. PubMed ID: 30542989
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Driver gene detection through Bayesian network integration of mutation and expression profiles.
    Chen Z; Lu Y; Cao B; Zhang W; Edwards A; Zhang K
    Bioinformatics; 2022 May; 38(10):2781-2790. PubMed ID: 35561191
    [TBL] [Abstract][Full Text] [Related]  

  • 7. DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network.
    Huang YE; Zhou S; Liu H; Zhou X; Yuan M; Hou F; Chen S; Chen J; Wang L; Jiang W
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36869849
    [TBL] [Abstract][Full Text] [Related]  

  • 8. LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.
    Wei PJ; Zhang D; Xia J; Zheng CH
    BMC Bioinformatics; 2016 Dec; 17(Suppl 17):467. PubMed ID: 28155630
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Novel Method for Identifying the Potential Cancer Driver Genes Based on Molecular Data Integration.
    Zhang W; Wang SL
    Biochem Genet; 2020 Feb; 58(1):16-39. PubMed ID: 31115714
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer.
    Lee CJ; Ahn H; Jeong D; Pak M; Moon JH; Kim S
    BMC Med Genomics; 2020 Feb; 13(Suppl 3):27. PubMed ID: 32093698
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Integrating mutation and gene expression cross-sectional data to infer cancer progression.
    Fleck JL; Pavel AB; Cassandras CG
    BMC Syst Biol; 2016 Jan; 10():12. PubMed ID: 26810975
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.
    Suo C; Hrydziuszko O; Lee D; Pramana S; Saputra D; Joshi H; Calza S; Pawitan Y
    Bioinformatics; 2015 Aug; 31(16):2607-13. PubMed ID: 25810432
    [TBL] [Abstract][Full Text] [Related]  

  • 13. KatzDriver: A network based method to cancer causal genes discovery in gene regulatory network.
    Akhavan-Safar M; Teimourpour B
    Biosystems; 2021 Mar; 201():104326. PubMed ID: 33309969
    [TBL] [Abstract][Full Text] [Related]  

  • 14. PRODIGY: personalized prioritization of driver genes.
    Dinstag G; Shamir R
    Bioinformatics; 2020 Mar; 36(6):1831-1839. PubMed ID: 31681944
    [TBL] [Abstract][Full Text] [Related]  

  • 15. m
    Ma Q; Zhang SW; Zhang SY
    Methods; 2022 Jul; 203():125-138. PubMed ID: 35436514
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Discovering potential cancer driver genes by an integrated network-based approach.
    Shi K; Gao L; Wang B
    Mol Biosyst; 2016 Aug; 12(9):2921-31. PubMed ID: 27426053
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Two-stage-vote ensemble framework based on integration of mutation data and gene interaction network for uncovering driver genes.
    Kan Y; Jiang L; Guo Y; Tang J; Guo F
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34791034
    [TBL] [Abstract][Full Text] [Related]  

  • 18. DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph.
    Wang C; Shi J; Cai J; Zhang Y; Zheng X; Zhang N
    BMC Bioinformatics; 2022 Jul; 23(1):277. PubMed ID: 35831792
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network.
    Liu C; Dai Y; Yu K; Zhang ZK
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2231-2240. PubMed ID: 33656997
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prioritization of cancer driver gene with prize-collecting steiner tree by introducing an edge weighted strategy in the personalized gene interaction network.
    Zhang SW; Wang ZN; Li Y; Guo WF
    BMC Bioinformatics; 2022 Aug; 23(1):341. PubMed ID: 35974311
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.