BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

263 related articles for article (PubMed ID: 36637211)

  • 1. Dealing with dimensionality: the application of machine learning to multi-omics data.
    Feldner-Busztin D; Firbas Nisantzis P; Edmunds SJ; Boza G; Racimo F; Gopalakrishnan S; Limborg MT; Lahti L; de Polavieja GG
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36637211
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep cross-omics cycle attention model for joint analysis of single-cell multi-omics data.
    Zuo C; Dai H; Chen L
    Bioinformatics; 2021 Nov; 37(22):4091-4099. PubMed ID: 34028557
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Clustering single-cell multi-omics data with MoClust.
    Yuan M; Chen L; Deng M
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36383167
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multi-project and Multi-profile joint Non-negative Matrix Factorization for cancer omic datasets.
    Salazar DA; Pržulj N; Valencia CF
    Bioinformatics; 2021 Dec; 37(24):4801-4809. PubMed ID: 34375392
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data.
    Hashim S; Nandakumar K; Yaqub M
    Pac Symp Biocomput; 2023; 28():263-274. PubMed ID: 36540983
    [TBL] [Abstract][Full Text] [Related]  

  • 6. PIntMF: Penalized Integrative Matrix Factorization method for multi-omics data.
    Pierre-Jean M; Mauger F; Deleuze JF; Le Floch E
    Bioinformatics; 2022 Jan; 38(4):900-907. PubMed ID: 34849583
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment.
    Cho HJ; Shu M; Bekiranov S; Zang C; Zhang A
    Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 36864611
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration.
    Wang X; Hu Z; Yu T; Wang Y; Wang R; Wei Y; Shu J; Ma J; Li Y
    Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 36975610
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning.
    Chen F; Zou G; Wu Y; Ou-Yang L
    Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38547401
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Cancer subtype identification by consensus guided graph autoencoders.
    Liang C; Shang M; Luo J
    Bioinformatics; 2021 Dec; 37(24):4779-4786. PubMed ID: 34289034
    [TBL] [Abstract][Full Text] [Related]  

  • 12. HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification.
    Wang H; Lin K; Zhang Q; Shi J; Song X; Wu J; Zhao C; He K
    Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38530977
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-omics data integration by generative adversarial network.
    Ahmed KT; Sun J; Cheng S; Yong J; Zhang W
    Bioinformatics; 2021 Dec; 38(1):179-186. PubMed ID: 34415323
    [TBL] [Abstract][Full Text] [Related]  

  • 14. NetProphet 3: a machine learning framework for transcription factor network mapping and multi-omics integration.
    Abid D; Brent MR
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36692138
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A supervised Bayesian factor model for the identification of multi-omics signatures.
    Gygi JP; Konstorum A; Pawar S; Aron E; Kleinstein SH; Guan L
    Bioinformatics; 2024 May; 40(5):. PubMed ID: 38603606
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification.
    Moon S; Lee H
    Bioinformatics; 2022 Apr; 38(8):2287-2296. PubMed ID: 35157023
    [TBL] [Abstract][Full Text] [Related]  

  • 17. COmic: convolutional kernel networks for interpretable end-to-end learning on (multi-)omics data.
    Ditz JC; Reuter B; Pfeifer N
    Bioinformatics; 2023 Jun; 39(39 Suppl 1):i76-i85. PubMed ID: 37387152
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Randomized singular value decomposition for integrative subtype analysis of 'omics data' using non-negative matrix factorization.
    Ni Y; He J; Chalise P
    Stat Appl Genet Mol Biol; 2023 Jan; 22(1):. PubMed ID: 37937887
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MRGCN: cancer subtyping with multi-reconstruction graph convolutional network using full and partial multi-omics dataset.
    Yang B; Yang Y; Wang M; Su X
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37255323
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data.
    Drouard G; Mykkänen J; Heiskanen J; Pohjonen J; Ruohonen S; Pahkala K; Lehtimäki T; Wang X; Ollikainen M; Ripatti S; Pirinen M; Raitakari O; Kaprio J
    BMC Med Inform Decis Mak; 2024 May; 24(1):116. PubMed ID: 38698395
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.