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 *

131 related articles for article (PubMed ID: 35579340)

  • 1. PersonaDrive: a method for the identification and prioritization of personalized cancer drivers.
    Erten C; Houdjedj A; Kazan H; Taleb Bahmed AA
    Bioinformatics; 2022 Jun; 38(13):3407-3414. PubMed ID: 35579340
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Ranking cancer drivers via betweenness-based outlier detection and random walks.
    Erten C; Houdjedj A; Kazan H
    BMC Bioinformatics; 2021 Feb; 22(1):62. PubMed ID: 33568049
    [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. A novel hypergraph model for identifying and prioritizing personalized drivers in cancer.
    Zhang N; Ma F; Guo D; Pang Y; Wang C; Zhang Y; Zheng X; Wang M
    PLoS Comput Biol; 2024 Apr; 20(4):e1012068. PubMed ID: 38683860
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. Identifying driver genes for individual patients through inductive matrix completion.
    Zhang T; Zhang SW; Li Y
    Bioinformatics; 2021 Dec; 37(23):4477-4484. PubMed ID: 34175939
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MODIG: integrating multi-omics and multi-dimensional gene network for cancer driver gene identification based on graph attention network model.
    Zhao W; Gu X; Chen S; Wu J; Zhou Z
    Bioinformatics; 2022 Oct; 38(21):4901-4907. PubMed ID: 36094338
    [TBL] [Abstract][Full Text] [Related]  

  • 11. MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules.
    Ahmed R; Baali I; Erten C; Hoxha E; Kazan H
    Bioinformatics; 2020 Feb; 36(3):872-879. PubMed ID: 31432076
    [TBL] [Abstract][Full Text] [Related]  

  • 12. pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers.
    Pham VVH; Liu L; Bracken CP; Nguyen T; Goodall GJ; Li J; Le TD
    Bioinformatics; 2021 Oct; 37(19):3285-3292. PubMed ID: 33904576
    [TBL] [Abstract][Full Text] [Related]  

  • 13. driveR: a novel method for prioritizing cancer driver genes using somatic genomics data.
    Ülgen E; Sezerman OU
    BMC Bioinformatics; 2021 May; 22(1):263. PubMed ID: 34030627
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Modeling gene-wise dependencies improves the identification of drug response biomarkers in cancer studies.
    Nikolova O; Moser R; Kemp C; Gönen M; Margolin AA
    Bioinformatics; 2017 May; 33(9):1362-1369. PubMed ID: 28082455
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology.
    Ulgen E; Ozisik O; Sezerman OU
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36689556
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Exploring gene-patient association to identify personalized cancer driver genes by linear neighborhood propagation.
    Huang Y; Chen F; Sun H; Zhong C
    BMC Bioinformatics; 2024 Jan; 25(1):34. PubMed ID: 38254011
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Personalized regression enables sample-specific pan-cancer analysis.
    Lengerich BJ; Aragam B; Xing EP
    Bioinformatics; 2018 Jul; 34(13):i178-i186. PubMed ID: 29949997
    [TBL] [Abstract][Full Text] [Related]  

  • 18. ContrastRank: a new method for ranking putative cancer driver genes and classification of tumor samples.
    Tian R; Basu MK; Capriotti E
    Bioinformatics; 2014 Sep; 30(17):i572-8. PubMed ID: 25161249
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Advancing cancer driver gene identification through an integrative network and pathway approach.
    Song J; Song Z; Gong Y; Ge L; Lou W
    J Biomed Inform; 2024 Oct; 158():104729. PubMed ID: 39306314
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.