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 *

175 related articles for article (PubMed ID: 37649392)

  • 21. EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.
    Parvandeh S; Donehower LA; Panagiotis K; Hsu TK; Asmussen JK; Lee K; Lichtarge O
    Nucleic Acids Res; 2022 Jul; 50(12):e70. PubMed ID: 35412634
    [TBL] [Abstract][Full Text] [Related]  

  • 22. DriverDBv3: a multi-omics database for cancer driver gene research.
    Liu SH; Shen PC; Chen CY; Hsu AN; Cho YC; Lai YL; Chen FH; Li CY; Wang SC; Chen M; Chung IF; Cheng WC
    Nucleic Acids Res; 2020 Jan; 48(D1):D863-D870. PubMed ID: 31701128
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Multi-omics integration analysis of GPCRs in pan-cancer to uncover inter-omics relationships and potential driver genes.
    Li S; Chen X; Chen J; Wu B; Liu J; Guo Y; Li M; Pu X
    Comput Biol Med; 2023 Jul; 161():106988. PubMed ID: 37201441
    [TBL] [Abstract][Full Text] [Related]  

  • 24. In silico saturation mutagenesis of cancer genes.
    Muiños F; Martínez-Jiménez F; Pich O; Gonzalez-Perez A; Lopez-Bigas N
    Nature; 2021 Aug; 596(7872):428-432. PubMed ID: 34321661
    [TBL] [Abstract][Full Text] [Related]  

  • 25. PATIENT-SPECIFIC DATA FUSION FOR CANCER STRATIFICATION AND PERSONALISED TREATMENT.
    Gligorijević V; Malod-Dognin N; Pržulj N
    Pac Symp Biocomput; 2016; 21():321-32. PubMed ID: 26776197
    [TBL] [Abstract][Full Text] [Related]  

  • 26. GLIMS: A two-stage gradual-learning method for cancer genes prediction using multi-omics data and co-splicing network.
    Niu R; Guo Y; Shang X
    iScience; 2024 Apr; 27(4):109387. PubMed ID: 38510118
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Ontology-based prediction of cancer driver genes.
    Althubaiti S; Karwath A; Dallol A; Noor A; Alkhayyat SS; Alwassia R; Mineta K; Gojobori T; Beggs AD; Schofield PN; Gkoutos GV; Hoehndorf R
    Sci Rep; 2019 Nov; 9(1):17405. PubMed ID: 31757986
    [TBL] [Abstract][Full Text] [Related]  

  • 28. 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]  

  • 29. 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]  

  • 30. Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.
    Raimondi D; Passemiers A; Fariselli P; Moreau Y
    BMC Biol; 2021 Jan; 19(1):3. PubMed ID: 33441128
    [TBL] [Abstract][Full Text] [Related]  

  • 31. 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]  

  • 32. Interactive gene identification for cancer subtyping based on multi-omics clustering.
    Ye X; Shi T; Cui Y; Sakurai T
    Methods; 2023 Mar; 211():61-67. PubMed ID: 36804215
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. Multi-Omic Data Improve Prediction of Personalized Tumor Suppressors and Oncogenes.
    Sudhakar M; Rengaswamy R; Raman K
    Front Genet; 2022; 13():854190. PubMed ID: 35620468
    [TBL] [Abstract][Full Text] [Related]  

  • 35. PhenoDriver: interpretable framework for studying personalized phenotype-associated driver genes in breast cancer.
    Li Y; Zhang SW; Xie MY; Zhang T
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37738403
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Applications of artificial intelligence multiomics in precision oncology.
    Srivastava R
    J Cancer Res Clin Oncol; 2023 Jan; 149(1):503-510. PubMed ID: 35796775
    [TBL] [Abstract][Full Text] [Related]  

  • 37. 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]  

  • 38. 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]  

  • 39. An Efficient and Easy-to-Use Network-Based Integrative Method of Multi-Omics Data for Cancer Genes Discovery.
    Wei T; Fa B; Luo C; Johnston L; Zhang Y; Yu Z
    Front Genet; 2020; 11():613033. PubMed ID: 33488678
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A denoised multi-omics integration framework for cancer subtype classification and survival prediction.
    Pang J; Liang B; Ding R; Yan Q; Chen R; Xu J
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37594302
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.