BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

324 related articles for article (PubMed ID: 37594302)

  • 1. 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]  

  • 2. Autoencoder-assisted latent representation learning for survival prediction and multi-view clustering on multi-omics cancer subtyping.
    Zhu S; Wang W; Fang W; Cui M
    Math Biosci Eng; 2023 Nov; 20(12):21098-21119. PubMed ID: 38124589
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A deep learning approach based on multi-omics data integration to construct a risk stratification prediction model for skin cutaneous melanoma.
    Li W; Huang Q; Peng Y; Pan S; Hu M; Wang P; He Y
    J Cancer Res Clin Oncol; 2023 Nov; 149(17):15923-15938. PubMed ID: 37673824
    [TBL] [Abstract][Full Text] [Related]  

  • 4. MOGAT: A Multi-Omics Integration Framework Using Graph Attention Networks for Cancer Subtype Prediction.
    Tanvir RB; Islam MM; Sobhan M; Luo D; Mondal AM
    Int J Mol Sci; 2024 Feb; 25(5):. PubMed ID: 38474033
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data.
    Zhao J; Zhao B; Song X; Lyu C; Chen W; Xiong Y; Wei DQ
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36702755
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A multimodal graph neural network framework for cancer molecular subtype classification.
    Li B; Nabavi S
    BMC Bioinformatics; 2024 Jan; 25(1):27. PubMed ID: 38225583
    [TBL] [Abstract][Full Text] [Related]  

  • 7. moSCminer: a cell subtype classification framework based on the attention neural network integrating the single-cell multi-omics dataset on the cloud.
    Choi JM; Park C; Chae H
    PeerJ; 2024; 12():e17006. PubMed ID: 38426141
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data.
    El-Manzalawy Y; Hsieh TY; Shivakumar M; Kim D; Honavar V
    BMC Med Genomics; 2018 Sep; 11(Suppl 3):71. PubMed ID: 30255801
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Capturing the latent space of an Autoencoder for multi-omics integration and cancer subtyping.
    Madhumita ; Paul S
    Comput Biol Med; 2022 Sep; 148():105832. PubMed ID: 35834966
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Integration of multi-omics data using adaptive graph learning and attention mechanism for patient classification and biomarker identification.
    Ouyang D; Liang Y; Li L; Ai N; Lu S; Yu M; Liu X; Xie S
    Comput Biol Med; 2023 Sep; 164():107303. PubMed ID: 37586201
    [TBL] [Abstract][Full Text] [Related]  

  • 11. HCNM: Heterogeneous Correlation Network Model for Multi-level Integrative Study of Multi-omics Data for Cancer Subtype Prediction.
    Vangimalla RR; Sreevalsan-Nair J
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():1880-1886. PubMed ID: 34891654
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data.
    Xu J; Wu P; Chen Y; Meng Q; Dawood H; Dawood H
    BMC Bioinformatics; 2019 Oct; 20(1):527. PubMed ID: 31660856
    [TBL] [Abstract][Full Text] [Related]  

  • 13. DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.
    Lan W; Liao H; Chen Q; Zhu L; Pan Y; Chen YP
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38678587
    [TBL] [Abstract][Full Text] [Related]  

  • 14. ProgCAE: a deep learning-based method that integrates multi-omics data to predict cancer subtypes.
    Liu Q; Song K
    Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37232375
    [TBL] [Abstract][Full Text] [Related]  

  • 15. moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networks.
    Choi JM; Chae H
    BMC Bioinformatics; 2023 Apr; 24(1):169. PubMed ID: 37101124
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ioSearch: An approach for identifying interacting multiomics biomarkers using a novel algorithm with application on breast cancer data sets.
    Das S; Srivastava DK
    Genet Epidemiol; 2023 Dec; 47(8):600-616. PubMed ID: 37795815
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer.
    Malik V; Kalakoti Y; Sundar D
    BMC Genomics; 2021 Mar; 22(1):214. PubMed ID: 33761889
    [TBL] [Abstract][Full Text] [Related]  

  • 18. DeFusion: a denoised network regularization framework for multi-omics integration.
    Wang W; Zhang X; Dai DQ
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33822879
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction.
    Zhang JZ; Xu W; Hu P
    Bioinformatics; 2022 Jun; 38(12):3259-3266. PubMed ID: 35445698
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MoGCN: A Multi-Omics Integration Method Based on Graph Convolutional Network for Cancer Subtype Analysis.
    Li X; Ma J; Leng L; Han M; Li M; He F; Zhu Y
    Front Genet; 2022; 13():806842. PubMed ID: 35186034
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.