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.
160 related articles for article (PubMed ID: 38426141)
1. moSCminer: a cell subtype classification framework based on the attention neural network integrating the single-cell multi-omics dataset on the cloud. Choi JM; Park C; Chae H PeerJ; 2024; 12():e17006. PubMed ID: 38426141 [TBL] [Abstract][Full Text] [Related]
2. moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networks. Choi JM; Chae H BMC Bioinformatics; 2023 Apr; 24(1):169. PubMed ID: 37101124 [TBL] [Abstract][Full Text] [Related]
3. A multimodal graph neural network framework for cancer molecular subtype classification. Li B; Nabavi S BMC Bioinformatics; 2024 Jan; 25(1):27. PubMed ID: 38225583 [TBL] [Abstract][Full Text] [Related]
4. MOGAT: A Multi-Omics Integration Framework Using Graph Attention Networks for Cancer Subtype Prediction. Tanvir RB; Islam MM; Sobhan M; Luo D; Mondal AM Int J Mol Sci; 2024 Feb; 25(5):. PubMed ID: 38474033 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. Multi-omics integration method based on attention deep learning network for biomedical data classification. Gong P; Cheng L; Zhang Z; Meng A; Li E; Chen J; Zhang L Comput Methods Programs Biomed; 2023 Apr; 231():107377. PubMed ID: 36739624 [TBL] [Abstract][Full Text] [Related]
7. Classifying breast cancer using multi-view graph neural network based on multi-omics data. Ren Y; Gao Y; Du W; Qiao W; Li W; Yang Q; Liang Y; Li G Front Genet; 2024; 15():1363896. PubMed ID: 38444760 [No Abstract] [Full Text] [Related]
8. A Contrastive-Learning-Based Deep Neural Network for Cancer Subtyping by Integrating Multi-Omics Data. Chai H; Deng W; Wei J; Guan T; He M; Liang Y; Li L Interdiscip Sci; 2024 Dec; 16(4):966-975. PubMed ID: 39230797 [TBL] [Abstract][Full Text] [Related]
9. MODILM: towards better complex diseases classification using a novel multi-omics data integration learning model. Zhong Y; Peng Y; Lin Y; Chen D; Zhang H; Zheng W; Chen Y; Wu C BMC Med Inform Decis Mak; 2023 May; 23(1):82. PubMed ID: 37147619 [TBL] [Abstract][Full Text] [Related]
10. A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data. Xu J; Wu P; Chen Y; Meng Q; Dawood H; Dawood H BMC Bioinformatics; 2019 Oct; 20(1):527. PubMed ID: 31660856 [TBL] [Abstract][Full Text] [Related]
11. GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype. Jeong D; Koo B; Oh M; Kim TB; Kim S Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37740295 [TBL] [Abstract][Full Text] [Related]
12. A denoised multi-omics integration framework for cancer subtype classification and survival prediction. Pang J; Liang B; Ding R; Yan Q; Chen R; Xu J Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37594302 [TBL] [Abstract][Full Text] [Related]
13. Subtype-MGTP: a cancer subtype identification framework based on multi-omics translation. Xie M; Kuang Y; Song M; Bao E Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38857453 [TBL] [Abstract][Full Text] [Related]
14. Subclassification of lung adenocarcinoma through comprehensive multi-omics data to benefit survival outcomes. Wei J; Wang X; Guo H; Zhang L; Shi Y; Wang X Comput Biol Chem; 2024 Oct; 112():108150. PubMed ID: 39018587 [TBL] [Abstract][Full Text] [Related]
15. NNBGWO-BRCA marker: Neural Network and binary grey wolf optimization based Breast cancer biomarker discovery framework using multi-omics dataset. Li M; Cai Y; Zhang M; Deng S; Wang L Comput Methods Programs Biomed; 2024 Sep; 254():108291. PubMed ID: 38909399 [TBL] [Abstract][Full Text] [Related]
16. MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data. Rong Z; Liu Z; Song J; Cao L; Yu Y; Qiu M; Hou Y Comput Biol Med; 2022 Nov; 150():106085. PubMed ID: 36162197 [TBL] [Abstract][Full Text] [Related]
17. HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification. Wang H; Lin K; Zhang Q; Shi J; Song X; Wu J; Zhao C; He K Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38530977 [TBL] [Abstract][Full Text] [Related]
18. Single-cell multi-omics integration for unpaired data by a siamese network with graph-based contrastive loss. Liu C; Wang L; Liu Z BMC Bioinformatics; 2023 Jan; 24(1):5. PubMed ID: 36600199 [TBL] [Abstract][Full Text] [Related]
19. Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data. Zhao J; Zhao B; Song X; Lyu C; Chen W; Xiong Y; Wei DQ Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36702755 [TBL] [Abstract][Full Text] [Related]
20. Integration of incomplete multi-omics data using Knowledge Distillation and Supervised Variational Autoencoders for disease progression prediction. Ranjbari S; Arslanturk S J Biomed Inform; 2023 Nov; 147():104512. PubMed ID: 37813325 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]