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 *

122 related articles for article (PubMed ID: 31966051)

  • 1. Identification of osteosarcoma driver genes using a network method.
    Si Z; Hu K
    Oncol Lett; 2020 Feb; 19(2):1215-1222. PubMed ID: 31966051
    [TBL] [Abstract][Full Text] [Related]  

  • 2. deepDriver: Predicting Cancer Driver Genes Based on Somatic Mutations Using Deep Convolutional Neural Networks.
    Luo P; Ding Y; Lei X; Wu FX
    Front Genet; 2019; 10():13. PubMed ID: 30761181
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Integrating omics data and protein interaction networks to prioritize driver genes in cancer.
    Zhang T; Zhang D
    Oncotarget; 2017 Aug; 8(35):58050-58060. PubMed ID: 28938536
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A support vector machine classifier for the prediction of osteosarcoma metastasis with high accuracy.
    He Y; Ma J; Ye X
    Int J Mol Med; 2017 Nov; 40(5):1357-1364. PubMed ID: 28901446
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Identification of differentially expressed genes in the development of osteosarcoma using RNA-seq.
    Yang Y; Zhang Y; Qu X; Xia J; Li D; Li X; Wang Y; He Z; Li S; Zhou Y; Xie L; Yang Z
    Oncotarget; 2016 Dec; 7(52):87194-87205. PubMed ID: 27888627
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Identifying driver genes involving gene dysregulated expression, tissue-specific expression and gene-gene network.
    Song J; Peng W; Wang F; Wang J
    BMC Med Genomics; 2019 Dec; 12(Suppl 7):168. PubMed ID: 31888619
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Network-Based Analysis of eQTL Data to Prioritize Driver Mutations.
    De Maeyer D; Weytjens B; De Raedt L; Marchal K
    Genome Biol Evol; 2016 Jan; 8(3):481-94. PubMed ID: 26802430
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Genomic heterogeneity of osteosarcoma - shift from single candidates to functional modules.
    Poos K; Smida J; Maugg D; Eckstein G; Baumhoer D; Nathrath M; Korsching E
    PLoS One; 2015; 10(4):e0123082. PubMed ID: 25848766
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.
    Lu X; Li X; Liu P; Qian X; Miao Q; Peng S
    Molecules; 2018 Jan; 23(2):. PubMed ID: 29364829
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray.
    Sun J; Xu H; Qi M; Zhang C; Shi J
    Mol Med Rep; 2019 Oct; 20(4):3075-3084. PubMed ID: 31432118
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Molecular genetics of osteosarcoma.
    Rickel K; Fang F; Tao J
    Bone; 2017 Sep; 102():69-79. PubMed ID: 27760307
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genome-wide analysis of somatic copy number alterations and chromosomal breakages in osteosarcoma.
    Smida J; Xu H; Zhang Y; Baumhoer D; Ribi S; Kovac M; von Luettichau I; Bielack S; O'Leary VB; Leib-Mösch C; Frishman D; Nathrath M
    Int J Cancer; 2017 Aug; 141(4):816-828. PubMed ID: 28494505
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.
    Gu H; Xu X; Qin P; Wang J
    Front Genet; 2020; 11():564839. PubMed ID: 33244318
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of different functional prediction scores using a gene-based permutation model for identifying cancer driver genes.
    Nono AD; Chen K; Liu X
    BMC Med Genomics; 2019 Jan; 12(Suppl 1):22. PubMed ID: 30704472
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The use of gene interaction networks to improve the identification of cancer driver genes.
    Ramsahai E; Walkins K; Tripathi V; John M
    PeerJ; 2017; 5():e2568. PubMed ID: 28149674
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.
    Gu Y; Wang H; Qin Y; Zhang Y; Zhao W; Qi L; Zhang Y; Wang C; Guo Z
    Mol Biosyst; 2013 Mar; 9(3):467-77. PubMed ID: 23344900
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.