BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

317 related articles for article (PubMed ID: 30853547)

  • 1. Unsupervised classification of multi-omics data during cardiac remodeling using deep learning.
    Chung NC; Mirza B; Choi H; Wang J; Wang D; Ping P; Wang W
    Methods; 2019 Aug; 166():66-73. PubMed ID: 30853547
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data.
    Rong Z; Liu Z; Song J; Cao L; Yu Y; Qiu M; Hou Y
    Comput Biol Med; 2022 Nov; 150():106085. PubMed ID: 36162197
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data.
    Withnell E; Zhang X; Sun K; Guo Y
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34402865
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.
    Wu D; Wang D; Zhang MQ; Gu J
    BMC Genomics; 2015 Dec; 16():1022. PubMed ID: 26626453
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multi-omics integration-a comparison of unsupervised clustering methodologies.
    Tini G; Marchetti L; Priami C; Scott-Boyer MP
    Brief Bioinform; 2019 Jul; 20(4):1269-1279. PubMed ID: 29272335
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computational frameworks integrating deep learning and statistical models in mining multimodal omics data.
    Lac L; Leung CK; Hu P
    J Biomed Inform; 2024 Apr; 152():104629. PubMed ID: 38552994
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Ensemble deep learning of embeddings for clustering multimodal single-cell omics data.
    Yu L; Liu C; Yang JYH; Yang P
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37314966
    [TBL] [Abstract][Full Text] [Related]  

  • 10. AVBAE-MODFR: A novel deep learning framework of embedding and feature selection on multi-omics data for pan-cancer classification.
    Li M; Guo H; Wang K; Kang C; Yin Y; Zhang H
    Comput Biol Med; 2024 Jul; 177():108614. PubMed ID: 38796884
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Clustering and variable selection evaluation of 13 unsupervised methods for multi-omics data integration.
    Pierre-Jean M; Deleuze JF; Le Floch E; Mauger F
    Brief Bioinform; 2020 Dec; 21(6):2011-2030. PubMed ID: 31792509
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Research on load clustering algorithm based on variational autoencoder and hierarchical clustering.
    Cai M; Zheng Y; Peng Z; Huang C; Jiang H
    PLoS One; 2024; 19(6):e0303977. PubMed ID: 38870191
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning-based clustering approaches for bioinformatics.
    Karim MR; Beyan O; Zappa A; Costa IG; Rebholz-Schuhmann D; Cochez M; Decker S
    Brief Bioinform; 2021 Jan; 22(1):393-415. PubMed ID: 32008043
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multi-omics integration method based on attention deep learning network for biomedical data classification.
    Gong P; Cheng L; Zhang Z; Meng A; Li E; Chen J; Zhang L
    Comput Methods Programs Biomed; 2023 Apr; 231():107377. PubMed ID: 36739624
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means.
    Hadipour H; Liu C; Davis R; Cardona ST; Hu P
    BMC Bioinformatics; 2022 Apr; 23(Suppl 4):132. PubMed ID: 35428173
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Strictly Unsupervised Deep Learning Method for HEp-2 Cell Image Classification.
    Vununu C; Lee SH; Kwon KR
    Sensors (Basel); 2020 May; 20(9):. PubMed ID: 32397567
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE).
    Ma T; Zhang A
    BMC Genomics; 2019 Dec; 20(Suppl 11):944. PubMed ID: 31856727
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification.
    Mansour RF; Escorcia-Gutierrez J; Gamarra M; Gupta D; Castillo O; Kumar S
    Pattern Recognit Lett; 2021 Nov; 151():267-274. PubMed ID: 34566223
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A benchmark study of deep learning-based multi-omics data fusion methods for cancer.
    Leng D; Zheng L; Wen Y; Zhang Y; Wu L; Wang J; Wang M; Zhang Z; He S; Bo X
    Genome Biol; 2022 Aug; 23(1):171. PubMed ID: 35945544
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.