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 *

111 related articles for article (PubMed ID: 37100024)

  • 1. Learning vector quantized representation for cancer subtypes identification.
    Chen Z; Yang Z; Zhu L; Gao P; Matsubara T; Kanaya S; Altaf-Ul-Amin M
    Comput Methods Programs Biomed; 2023 Jun; 236():107543. PubMed ID: 37100024
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping.
    Ge S; Liu J; Cheng Y; Meng X; Wang X
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36445207
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Deeply integrating latent consistent representations in high-noise multi-omics data for cancer subtyping.
    Cai Y; Wang S
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38426322
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data.
    Yang Z; Zhu L; Chen Z; Huang M; Ono N; Altaf-Ul-Amin MD; Kanaya S
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1113-1116. PubMed ID: 36085834
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. 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]  

  • 8. Integrated multi-omics analysis of ovarian cancer using variational autoencoders.
    Hira MT; Razzaque MA; Angione C; Scrivens J; Sawan S; Sarker M
    Sci Rep; 2021 Mar; 11(1):6265. PubMed ID: 33737557
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Weighted dimensionality reduction and robust Gaussian mixture model based cancer patient subtyping from gene expression data.
    Rafique O; Mir AH
    J Biomed Inform; 2020 Dec; 112():103620. PubMed ID: 33188907
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Benchmarking variational AutoEncoders on cancer transcriptomics data.
    Eltager M; Abdelaal T; Charrout M; Mahfouz A; Reinders MJT; Makrodimitris S
    PLoS One; 2023; 18(10):e0292126. PubMed ID: 37796856
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pathway-based deep clustering for molecular subtyping of cancer.
    Mallavarapu T; Hao J; Kim Y; Oh JH; Kang M
    Methods; 2020 Feb; 173():24-31. PubMed ID: 31247294
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Robust correlation estimation and UMAP assisted topological analysis of omics data for disease subtyping.
    Rather AA; Chachoo MA
    Comput Biol Med; 2023 Mar; 155():106640. PubMed ID: 36774889
    [TBL] [Abstract][Full Text] [Related]  

  • 13. MODEC: an unsupervised clustering method integrating omics data for identifying cancer subtypes.
    Zhang Y; Kiryu H
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36094092
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.
    Mo Q; Shen R; Guo C; Vannucci M; Chan KS; Hilsenbeck SG
    Biostatistics; 2018 Jan; 19(1):71-86. PubMed ID: 28541380
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PathME: pathway based multi-modal sparse autoencoders for clustering of patient-level multi-omics data.
    Lemsara A; Ouadfel S; Fröhlich H
    BMC Bioinformatics; 2020 Apr; 21(1):146. PubMed ID: 32299344
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Subtype-WESLR: identifying cancer subtype with weighted ensemble sparse latent representation of multi-view data.
    Song W; Wang W; Dai DQ
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34607358
    [TBL] [Abstract][Full Text] [Related]  

  • 17. VPAC: Variational projection for accurate clustering of single-cell transcriptomic data.
    Chen S; Hua K; Cui H; Jiang R
    BMC Bioinformatics; 2019 May; 20(Suppl 7):0. PubMed ID: 31074382
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning-based ovarian cancer subtypes identification using multi-omics data.
    Guo LY; Wu AH; Wang YX; Zhang LP; Chai H; Liang XF
    BioData Min; 2020; 13():10. PubMed ID: 32863885
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.
    Liang M; Li Z; Chen T; Zeng J
    IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(4):928-37. PubMed ID: 26357333
    [TBL] [Abstract][Full Text] [Related]  

  • 20. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.
    Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.