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 *

177 related articles for article (PubMed ID: 37551622)

  • 1. A workflow to study mechanistic indicators for driver gene prediction with Moonlight.
    Nourbakhsh M; Saksager A; Tom N; Chen XS; Colaprico A; Olsen C; Tiberti M; Papaleo E
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37551622
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Interpreting pathways to discover cancer driver genes with Moonlight.
    Colaprico A; Olsen C; Bailey MH; Odom GJ; Terkelsen T; Silva TC; Olsen AV; Cantini L; Zinovyev A; Barillot E; Noushmehr H; Bertoli G; Castiglioni I; Cava C; Bontempi G; Chen XS; Papaleo E
    Nat Commun; 2020 Jan; 11(1):69. PubMed ID: 31900418
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identifying cancer type specific oncogenes and tumor suppressors using limited size data.
    Pavel AB; Vasile CI
    J Bioinform Comput Biol; 2016 Dec; 14(6):1650031. PubMed ID: 27712196
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Uncovering driver genes in breast cancer through an innovative machine learning mutational analysis method.
    Taheri G; Habibi M
    Comput Biol Med; 2024 Mar; 171():108234. PubMed ID: 38430742
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
    Agajanian S; Odeyemi O; Bischoff N; Ratra S; Verkhivker GM
    J Chem Inf Model; 2018 Oct; 58(10):2131-2150. PubMed ID: 30253099
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. Use of signals of positive and negative selection to distinguish cancer genes and passenger genes.
    Bányai L; Trexler M; Kerekes K; Csuka O; Patthy L
    Elife; 2021 Jan; 10():. PubMed ID: 33427197
    [TBL] [Abstract][Full Text] [Related]  

  • 11. DriverGroup: a novel method for identifying driver gene groups.
    Pham VVH; Liu L; Bracken CP; Goodall GJ; Li J; Le TD
    Bioinformatics; 2020 Dec; 36(Suppl_2):i583-i591. PubMed ID: 33381812
    [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. Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer.
    Silva GO; He X; Parker JS; Gatza ML; Carey LA; Hou JP; Moulder SL; Marcom PK; Ma J; Rosen JM; Perou CM
    Breast Cancer Res Treat; 2015 Jul; 152(2):347-56. PubMed ID: 26109346
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. The cancer driver genes IDH1/2, JARID1C/ KDM5C, and UTX/ KDM6A: crosstalk between histone demethylation and hypoxic reprogramming in cancer metabolism.
    Chang S; Yim S; Park H
    Exp Mol Med; 2019 Jun; 51(6):1-17. PubMed ID: 31221981
    [TBL] [Abstract][Full Text] [Related]  

  • 17. SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.
    Van den Eynden J; Fierro AC; Verbeke LP; Marchal K
    BMC Bioinformatics; 2015 Apr; 16():125. PubMed ID: 25903787
    [TBL] [Abstract][Full Text] [Related]  

  • 18. OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.
    Wang T; Ruan S; Zhao X; Shi X; Teng H; Zhong J; You M; Xia K; Sun Z; Mao F
    Nucleic Acids Res; 2021 Jan; 49(D1):D1289-D1301. PubMed ID: 33179738
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. A new machine learning method for cancer mutation analysis.
    Habibi M; Taheri G
    PLoS Comput Biol; 2022 Oct; 18(10):e1010332. PubMed ID: 36251702
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.