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 *

136 related articles for article (PubMed ID: 30990192)

  • 1. MCNF: A Novel Method for Cancer Subtyping by Integrating Multi-Omics and Clinical Data.
    Zhao L; Yan H
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1682-1690. PubMed ID: 30990192
    [TBL] [Abstract][Full Text] [Related]  

  • 2. WMLRR: A Weighted Multi-View Low Rank Representation to Identify Cancer Subtypes From Multiple Types of Omics Data.
    Sun Y; Ou-Yang L; Dai DQ
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(6):2891-2897. PubMed ID: 33656995
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation and comparison of multi-omics data integration methods for cancer subtyping.
    Duan R; Gao L; Gao Y; Hu Y; Xu H; Huang M; Song K; Wang H; Dong Y; Jiang C; Zhang C; Jia S
    PLoS Comput Biol; 2021 Aug; 17(8):e1009224. PubMed ID: 34383739
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping.
    Yang H; Zhao L; Li D; An C; Fang X; Chen Y; Liu J; Xiao T; Wang Z
    Cell Rep Methods; 2024 Jun; 4(6):100781. PubMed ID: 38761803
    [TBL] [Abstract][Full Text] [Related]  

  • 5. PCA-constrained multi-core matrix fusion network: A novel approach for cancer subtype identification.
    Li M; Qi Z; Liu L; Lou M; Deng S
    J Bioinform Comput Biol; 2024 Aug; 22(4):2450014. PubMed ID: 39183679
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning.
    Wei Y; Li L; Zhao X; Yang H; Sa J; Cao H; Cui Y
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36433785
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.
    Heo YJ; Hwa C; Lee GH; Park JM; An JY
    Mol Cells; 2021 Jul; 44(7):433-443. PubMed ID: 34238766
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival.
    Ramazzotti D; Lal A; Wang B; Batzoglou S; Sidow A
    Nat Commun; 2018 Oct; 9(1):4453. PubMed ID: 30367051
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.
    Jilani M; Degras D; Haspel N
    Genes (Basel); 2024 May; 15(5):. PubMed ID: 38790260
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas.
    van IJzendoorn DGP; Szuhai K; Briaire-de Bruijn IH; Kostine M; Kuijjer ML; Bovée JVMG
    PLoS Comput Biol; 2019 Feb; 15(2):e1006826. PubMed ID: 30785874
    [TBL] [Abstract][Full Text] [Related]  

  • 13. NESM: a network embedding method for tumor stratification by integrating multi-omics data.
    Li F; Sun Z; Liu JX; Shang J; Dai L; Liu X; Li Y
    G3 (Bethesda); 2022 Nov; 12(11):. PubMed ID: 36124952
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus.
    Cai M; Li L
    BMC Med Genomics; 2017 Dec; 10(Suppl 4):75. PubMed ID: 29322925
    [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. Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.
    Peng C; Zheng Y; Huang DS
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1605-1612. PubMed ID: 30969931
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.
    Moon M; Nakai K
    J Bioinform Comput Biol; 2018 Apr; 16(2):1850006. PubMed ID: 29566639
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets.
    Wei Z; Zhang Y; Weng W; Chen J; Cai H
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32533167
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Discriminant Projection Shared Dictionary Learning for Classification of Tumors Using Gene Expression Data.
    Peng S; Yang Y; Liu W; Li F; Liao X
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(4):1464-1473. PubMed ID: 31675339
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.