316 related articles for article (PubMed ID: 37586201)
1. Integration of multi-omics data using adaptive graph learning and attention mechanism for patient classification and biomarker identification.
Ouyang D; Liang Y; Li L; Ai N; Lu S; Yu M; Liu X; Xie S
Comput Biol Med; 2023 Sep; 164():107303. PubMed ID: 37586201
[TBL] [Abstract][Full Text] [Related]
2. 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]
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. Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration.
Yin C; Cao Y; Sun P; Zhang H; Li Z; Xu Y; Sun H
Front Genet; 2022; 13():884028. PubMed ID: 35646077
[TBL] [Abstract][Full Text] [Related]
5. CLCLSA: Cross-omics linked embedding with contrastive learning and self attention for integration with incomplete multi-omics data.
Zhao C; Liu A; Zhang X; Cao X; Ding Z; Sha Q; Shen H; Deng HW; Zhou W
Comput Biol Med; 2024 Mar; 170():108058. PubMed ID: 38295477
[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. 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]
8. TEMINET: A Co-Informative and Trustworthy Multi-Omics Integration Network for Diagnostic Prediction.
Luo H; Liang H; Liu H; Fan Z; Wei Y; Yao X; Cong S
Int J Mol Sci; 2024 Jan; 25(3):. PubMed ID: 38338932
[TBL] [Abstract][Full Text] [Related]
9. AVBAE-MODFR: A novel deep learning framework of embedding and feature selection on multi-omics data for pan-cancer classification.
Li M; Guo H; Wang K; Kang C; Yin Y; Zhang H
Comput Biol Med; 2024 Jul; 177():108614. PubMed ID: 38796884
[TBL] [Abstract][Full Text] [Related]
10. FGCNSurv: dually fused graph convolutional network for multi-omics survival prediction.
Wen G; Li L
Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37522887
[TBL] [Abstract][Full Text] [Related]
11. CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data.
Zhao C; Liu A; Zhang X; Cao X; Ding Z; Sha Q; Shen H; Deng HW; Zhou W
Res Sq; 2023 May; ():. PubMed ID: 37205427
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. IMOVNN: incomplete multi-omics data integration variational neural networks for gut microbiome disease prediction and biomarker identification.
Hu M; Zhu J; Peng G; Lu W; Wang H; Xie Z
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37930027
[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. Uncertainty-aware dynamic integration for multi-omics classification of tumors.
Du L; Liu C; Wei R; Chen J
J Cancer Res Clin Oncol; 2023 Jul; 149(7):3301-3312. PubMed ID: 35925427
[TBL] [Abstract][Full Text] [Related]
16. Graph Neural Networks With Multiple Prior Knowledge for Multi-Omics Data Analysis.
Xiao S; Lin H; Wang C; Wang S; Rajapakse JC
IEEE J Biomed Health Inform; 2023 Sep; 27(9):4591-4600. PubMed ID: 37307177
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Local augmented graph neural network for multi-omics cancer prognosis prediction and analysis.
Zhang Y; Xiong S; Wang Z; Liu Y; Luo H; Li B; Zou Q
Methods; 2023 May; 213():1-9. PubMed ID: 36933628
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]
