155 related articles for article (PubMed ID: 31444786)
1. Integrative factorization of bidimensionally linked matrices.
Park JY; Lock EF
Biometrics; 2020 Mar; 76(1):61-74. PubMed ID: 31444786
[TBL] [Abstract][Full Text] [Related]
2. BIDIMENSIONAL LINKED MATRIX FACTORIZATION FOR PAN-OMICS PAN-CANCER ANALYSIS.
Lock EF; Park JY; Hoadley KA
Ann Appl Stat; 2022 Mar; 16(1):193-215. PubMed ID: 35505906
[TBL] [Abstract][Full Text] [Related]
3. A hierarchical spike-and-slab model for pan-cancer survival using pan-omic data.
Samorodnitsky S; Hoadley KA; Lock EF
BMC Bioinformatics; 2022 Jun; 23(1):235. PubMed ID: 35710340
[TBL] [Abstract][Full Text] [Related]
4. Linked matrix factorization.
O'Connell MJ; Lock EF
Biometrics; 2019 Jun; 75(2):582-592. PubMed ID: 30516272
[TBL] [Abstract][Full Text] [Related]
5. Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer.
Ponzi E; Thoresen M; Haugdahl Nøst T; Møllersen K
BMC Bioinformatics; 2021 Aug; 22(1):395. PubMed ID: 34353282
[TBL] [Abstract][Full Text] [Related]
6. A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis.
Witten DM; Tibshirani R; Hastie T
Biostatistics; 2009 Jul; 10(3):515-34. PubMed ID: 19377034
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Multiple augmented reduced rank regression for pan-cancer analysis.
Wang J; Lock EF
Biometrics; 2024 Jan; 80(1):. PubMed ID: 38281771
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Hierarchical nuclear norm penalization for multi-view data integration.
Yi S; Wong RKW; Gaynanova I
Biometrics; 2023 Dec; 79(4):2933-2946. PubMed ID: 37345491
[TBL] [Abstract][Full Text] [Related]
12. Structural learning and integrative decomposition of multi-view data.
Gaynanova I; Li G
Biometrics; 2019 Dec; 75(4):1121-1132. PubMed ID: 31254385
[TBL] [Abstract][Full Text] [Related]
13. Latent Feature Decompositions for Integrative Analysis of Multi-Platform Genomic Data.
Gregory KB; Momin AA; Coombes KR; Baladandayuthapani V
IEEE/ACM Trans Comput Biol Bioinform; 2014; 11(6):984-94. PubMed ID: 26146492
[TBL] [Abstract][Full Text] [Related]
14. Integrative multi-view regression: Bridging group-sparse and low-rank models.
Li G; Liu X; Chen K
Biometrics; 2019 Jun; 75(2):593-602. PubMed ID: 30456759
[TBL] [Abstract][Full Text] [Related]
15. Joint principal trend analysis for longitudinal high-dimensional data.
Zhang Y; Ouyang Z
Biometrics; 2018 Jun; 74(2):430-438. PubMed ID: 28759699
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Methods of selecting informative variables.
Fedorov VV; Herzberg AM; Leonov SL
Biom J; 2006 Feb; 48(1):157-73. PubMed ID: 16544821
[TBL] [Abstract][Full Text] [Related]
18. Network-based penalized regression with application to genomic data.
Kim S; Pan W; Shen X
Biometrics; 2013 Sep; 69(3):582-93. PubMed ID: 23822182
[TBL] [Abstract][Full Text] [Related]
19. Bayesian variable selection with graphical structure learning: Applications in integrative genomics.
Kundu S; Cheng Y; Shin M; Manyam G; Mallick BK; Baladandayuthapani V
PLoS One; 2018; 13(7):e0195070. PubMed ID: 30059495
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]