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.
227 related articles for article (PubMed ID: 34289034)
1. 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]
2. Autoencoder-assisted latent representation learning for survival prediction and multi-view clustering on multi-omics cancer subtyping. Zhu S; Wang W; Fang W; Cui M Math Biosci Eng; 2023 Nov; 20(12):21098-21119. PubMed ID: 38124589 [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. 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]
5. GMHCC: high-throughput analysis of biomolecular data using graph-based multiple hierarchical consensus clustering. Lu Y; Yu Z; Wang Y; Ma Z; Wong KC; Li X Bioinformatics; 2022 May; 38(11):3020-3028. PubMed ID: 35451457 [TBL] [Abstract][Full Text] [Related]
6. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering. Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596 [TBL] [Abstract][Full Text] [Related]
7. 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]
8. Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping. Ge S; Liu J; Cheng Y; Meng X; Wang X Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36445207 [TBL] [Abstract][Full Text] [Related]
9. Multiview Robust Graph-Based Clustering for Cancer Subtype Identification. Shi X; Liang C; Wang H IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):544-556. PubMed ID: 35044919 [TBL] [Abstract][Full Text] [Related]
10. MultiGATAE: A Novel Cancer Subtype Identification Method Based on Multi-Omics and Attention Mechanism. Zhang G; Peng Z; Yan C; Wang J; Luo J; Luo H Front Genet; 2022; 13():855629. PubMed ID: 35391797 [TBL] [Abstract][Full Text] [Related]
11. 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]
12. Multi-omics data fusion using adaptive GTO guided Non-negative matrix factorization for cancer subtype discovery. Bansal B; Sahoo A Comput Methods Programs Biomed; 2023 Jan; 228():107246. PubMed ID: 36434961 [TBL] [Abstract][Full Text] [Related]
13. NEMO: cancer subtyping by integration of partial multi-omic data. Rappoport N; Shamir R Bioinformatics; 2019 Sep; 35(18):3348-3356. PubMed ID: 30698637 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Multi-View Spectral Clustering Based on Multi-Smooth Representation Fusion for Cancer Subtype Prediction. Liu J; Ge S; Cheng Y; Wang X Front Genet; 2021; 12():718915. PubMed ID: 34552619 [TBL] [Abstract][Full Text] [Related]
17. Deep multi-omics integration by learning correlation-maximizing representation identifies prognostically stratified cancer subtypes. Ji Y; Dutta P; Davuluri R Bioinform Adv; 2023; 3(1):vbad075. PubMed ID: 37424943 [TBL] [Abstract][Full Text] [Related]
18. Consensus clustering applied to multi-omics disease subtyping. Brière G; Darbo É; Thébault P; Uricaru R BMC Bioinformatics; 2021 Jul; 22(1):361. PubMed ID: 34229612 [TBL] [Abstract][Full Text] [Related]
19. Multi-omics clustering for cancer subtyping based on latent subspace learning. Ye X; Shang Y; Shi T; Zhang W; Sakurai T Comput Biol Med; 2023 Sep; 164():107223. PubMed ID: 37490833 [TBL] [Abstract][Full Text] [Related]
20. A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks. Wang J; Liao N; Du X; Chen Q; Wei B BMC Genomics; 2024 Jan; 25(1):86. PubMed ID: 38254021 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]