BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

200 related articles for article (PubMed ID: 25192743)

  • 1. Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation.
    Xu Y; Guo X; Sun J; Zhao Z
    Bioinformatics; 2015 Jan; 31(1):84-93. PubMed ID: 25192743
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient methods for identifying mutated driver pathways in cancer.
    Zhao J; Zhang S; Wu LY; Zhang XS
    Bioinformatics; 2012 Nov; 28(22):2940-7. PubMed ID: 22982574
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Driver gene mutations based clustering of tumors: methods and applications.
    Zhang W; Flemington EK; Zhang K
    Bioinformatics; 2018 Jul; 34(13):i404-i411. PubMed ID: 29950003
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analysis of 7,815 cancer exomes reveals associations between mutational processes and somatic driver mutations.
    Poulos RC; Wong YT; Ryan R; Pang H; Wong JWH
    PLoS Genet; 2018 Nov; 14(11):e1007779. PubMed ID: 30412573
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.
    Yang H; Wei Q; Zhong X; Yang H; Li B
    Bioinformatics; 2017 Feb; 33(4):483-490. PubMed ID: 27797769
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Discovering personalized driver mutation profiles of single samples in cancer by network control strategy.
    Guo WF; Zhang SW; Liu LL; Liu F; Shi QQ; Zhang L; Tang Y; Zeng T; Chen L
    Bioinformatics; 2018 Jun; 34(11):1893-1903. PubMed ID: 29329368
    [TBL] [Abstract][Full Text] [Related]  

  • 7. In-depth genomic data analyses revealed complex transcriptional and epigenetic dysregulations of BRAFV600E in melanoma.
    Guo X; Xu Y; Zhao Z
    Mol Cancer; 2015 Mar; 14():60. PubMed ID: 25890285
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identifying cancer driver genes in tumor genome sequencing studies.
    Youn A; Simon R
    Bioinformatics; 2011 Jan; 27(2):175-81. PubMed ID: 21169372
    [TBL] [Abstract][Full Text] [Related]  

  • 9. LowMACA: exploiting protein family analysis for the identification of rare driver mutations in cancer.
    Melloni GE; de Pretis S; Riva L; Pelizzola M; Céol A; Costanza J; Müller H; Zammataro L
    BMC Bioinformatics; 2016 Feb; 17():80. PubMed ID: 26860319
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.
    Kumar S; Warrell J; Li S; McGillivray PD; Meyerson W; Salichos L; Harmanci A; Martinez-Fundichely A; Chan CWY; Nielsen MM; Lochovsky L; Zhang Y; Li X; Lou S; Pedersen JS; Herrmann C; Getz G; Khurana E; Gerstein MB
    Cell; 2020 Mar; 180(5):915-927.e16. PubMed ID: 32084333
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Novel Approach to Evaluating Cancer Driver Gene Mutation Densities: Cytoskeleton-related Gene Candidates.
    Fawcett TJ; Parry ML; Blanck G
    Cancer Genomics Proteomics; 2015; 12(6):283-90. PubMed ID: 26543077
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis.
    Li A; Chapuy B; Varelas X; Sebastiani P; Monti S
    Sci Rep; 2019 Nov; 9(1):16904. PubMed ID: 31729402
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Simultaneous identification of multiple driver pathways in cancer.
    Leiserson MD; Blokh D; Sharan R; Raphael BJ
    PLoS Comput Biol; 2013; 9(5):e1003054. PubMed ID: 23717195
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Predicting the functional consequences of cancer-associated amino acid substitutions.
    Shihab HA; Gough J; Cooper DN; Day IN; Gaunt TR
    Bioinformatics; 2013 Jun; 29(12):1504-10. PubMed ID: 23620363
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Cancer systems biology of TCGA SKCM: efficient detection of genomic drivers in melanoma.
    Guan J; Gupta R; Filipp FV
    Sci Rep; 2015 Jan; 5():7857. PubMed ID: 25600636
    [TBL] [Abstract][Full Text] [Related]  

  • 20. De novo discovery of mutated driver pathways in cancer.
    Vandin F; Upfal E; Raphael BJ
    Genome Res; 2012 Feb; 22(2):375-85. PubMed ID: 21653252
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.