BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

171 related articles for article (PubMed ID: 32714868)

  • 1. A Novel Method for Cancer Subtyping and Risk Prediction Using Consensus Factor Analysis.
    Tran D; Nguyen H; Le U; Bebis G; Luu HN; Nguyen T
    Front Oncol; 2020; 10():1052. PubMed ID: 32714868
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SMRT: Randomized Data Transformation for Cancer Subtyping and Big Data Analysis.
    Nguyen H; Tran D; Tran B; Roy M; Cassell A; Dascalu S; Draghici S; Nguyen T
    Front Oncol; 2021; 11():725133. PubMed ID: 34745946
    [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. Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data.
    Yang H; Chen R; Li D; Wang Z
    Bioinformatics; 2021 Aug; 37(16):2231-2237. PubMed ID: 33599254
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data.
    Liu Q; Cheng B; Jin Y; Hu P
    J Biomed Inform; 2022 Jan; 125():103958. PubMed ID: 34839017
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A novel approach for data integration and disease subtyping.
    Nguyen T; Tagett R; Diaz D; Draghici S
    Genome Res; 2017 Dec; 27(12):2025-2039. PubMed ID: 29066617
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. CEPICS: A Comparison and Evaluation Platform for Integration Methods in Cancer Subtyping.
    Duan R; Gao L; Xu H; Song K; Hu Y; Wang H; Dong Y; Zhang C; Jia S
    Front Genet; 2019; 10():966. PubMed ID: 31649733
    [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. Deep structure integrative representation of multi-omics data for cancer subtyping.
    Yang B; Yang Y; Su X
    Bioinformatics; 2022 Jun; 38(13):3337-3342. PubMed ID: 35639657
    [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. Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration.
    Yin C; Cao Y; Sun P; Zhang H; Li Z; Xu Y; Sun H
    Front Genet; 2022; 13():884028. PubMed ID: 35646077
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-Omics Data Fusion for Cancer Molecular Subtyping Using Sparse Canonical Correlation Analysis.
    Qi L; Wang W; Wu T; Zhu L; He L; Wang X
    Front Genet; 2021; 12():607817. PubMed ID: 34367231
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Supervised Graph Clustering for Cancer Subtyping Based on Survival Analysis and Integration of Multi-Omic Tumor Data.
    Liu C; Cao W; Wu S; Shen W; Jiang D; Yu Z; Wong HS
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(2):1193-1202. PubMed ID: 32750893
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data.
    Franco EF; Rana P; Cruz A; Calderón VV; Azevedo V; Ramos RTJ; Ghosh P
    Cancers (Basel); 2021 Apr; 13(9):. PubMed ID: 33921978
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.
    Takahashi S; Asada K; Takasawa K; Shimoyama R; Sakai A; Bolatkan A; Shinkai N; Kobayashi K; Komatsu M; Kaneko S; Sese J; Hamamoto R
    Biomolecules; 2020 Oct; 10(10):. PubMed ID: 33086649
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Simultaneous discovery of cancer subtypes and subtype features by molecular data integration.
    Le Van T; van Leeuwen M; Carolina Fierro A; De Maeyer D; Van den Eynden J; Verbeke L; De Raedt L; Marchal K; Nijssen S
    Bioinformatics; 2016 Sep; 32(17):i445-i454. PubMed ID: 27587661
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer: Results from Multiple Cohorts, Including TCGA.
    Morera DS; Hasanali SL; Belew D; Ghosh S; Klaassen Z; Jordan AR; Wang J; Terris MK; Bollag RJ; Merseburger AS; Stenzl A; Soloway MS; Lokeshwar VB
    J Urol; 2020 Jan; 203(1):62-72. PubMed ID: 31112107
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A hierarchical clustering and data fusion approach for disease subtype discovery.
    Pfeifer B; Schimek MG
    J Biomed Inform; 2021 Jan; 113():103636. PubMed ID: 33271342
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.