262 related articles for article (PubMed ID: 26377073)
1. A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data.
Yang Z; Michailidis G
Bioinformatics; 2016 Jan; 32(1):1-8. PubMed ID: 26377073
[TBL] [Abstract][Full Text] [Related]
2. Identifying multi-layer gene regulatory modules from multi-dimensional genomic data.
Li W; Zhang S; Liu CC; Zhou XJ
Bioinformatics; 2012 Oct; 28(19):2458-66. PubMed ID: 22863767
[TBL] [Abstract][Full Text] [Related]
3. A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules.
Zhang S; Li Q; Liu J; Zhou XJ
Bioinformatics; 2011 Jul; 27(13):i401-9. PubMed ID: 21685098
[TBL] [Abstract][Full Text] [Related]
4. Discovery of microRNAs and Transcription Factors Co-Regulatory Modules by Integrating Multiple Types of Genomic Data.
Luo J; Xiang G; Pan C
IEEE Trans Nanobioscience; 2017 Jan; 16(1):51-59. PubMed ID: 28092569
[TBL] [Abstract][Full Text] [Related]
5. jNMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data.
Wang HQ; Zheng CH; Zhao XM
Bioinformatics; 2015 Feb; 31(4):572-80. PubMed ID: 25411328
[TBL] [Abstract][Full Text] [Related]
6. Discovery of multi-dimensional modules by integrative analysis of cancer genomic data.
Zhang S; Liu CC; Li W; Shen H; Laird PW; Zhou XJ
Nucleic Acids Res; 2012 Oct; 40(19):9379-91. PubMed ID: 22879375
[TBL] [Abstract][Full Text] [Related]
7. SOJNMF: Identifying Multidimensional Molecular Regulatory Modules by Sparse Orthogonality-Regularized Joint Non-Negative Matrix Factorization Algorithm.
Wang Y; Guan T; Zhou G; Zhao H; Gao J
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3695-3703. PubMed ID: 34546925
[TBL] [Abstract][Full Text] [Related]
8. Bayesian joint analysis of heterogeneous genomics data.
Ray P; Zheng L; Lucas J; Carin L
Bioinformatics; 2014 May; 30(10):1370-6. PubMed ID: 24489367
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. scMNMF: a novel method for single-cell multi-omics clustering based on matrix factorization.
Qiu Y; Guo D; Zhao P; Zou Q
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38754408
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. DeepMF: deciphering the latent patterns in omics profiles with a deep learning method.
Chen L; Xu J; Li SC
BMC Bioinformatics; 2019 Dec; 20(Suppl 23):648. PubMed ID: 31881818
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder.
Wang HQ; Li HL; Han JL; Feng ZP; Deng HX; Han X
Comput Biol Chem; 2023 Aug; 105():107906. PubMed ID: 37336028
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of hierarchical models for integrative genomic analyses.
Denis M; Tadesse MG
Bioinformatics; 2016 Mar; 32(5):738-46. PubMed ID: 26545823
[TBL] [Abstract][Full Text] [Related]
17. Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.
Tong L; Wu H; Wang MD
Methods; 2021 May; 189():74-85. PubMed ID: 32763377
[TBL] [Abstract][Full Text] [Related]
18. Integrative cancer patient stratification via subspace merging.
Ding H; Sharpnack M; Wang C; Huang K; Machiraju R
Bioinformatics; 2019 May; 35(10):1653-1659. PubMed ID: 30329022
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of integrative clustering methods for the analysis of multi-omics data.
Chauvel C; Novoloaca A; Veyre P; Reynier F; Becker J
Brief Bioinform; 2020 Mar; 21(2):541-552. PubMed ID: 31220206
[TBL] [Abstract][Full Text] [Related]
20. CeModule: an integrative framework for discovering regulatory patterns from genomic data in cancer.
Xiao Q; Luo J; Liang C; Cai J; Li G; Cao B
BMC Bioinformatics; 2019 Feb; 20(1):67. PubMed ID: 30732558
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]