158 related articles for article (PubMed ID: 33897768)
1. PMDFI: Predicting miRNA-Disease Associations Based on High-Order Feature Interaction.
Tang M; Liu C; Liu D; Liu J; Liu J; Deng L
Front Genet; 2021; 12():656107. PubMed ID: 33897768
[TBL] [Abstract][Full Text] [Related]
2. An improved random forest-based computational model for predicting novel miRNA-disease associations.
Yao D; Zhan X; Kwoh CK
BMC Bioinformatics; 2019 Dec; 20(1):624. PubMed ID: 31795954
[TBL] [Abstract][Full Text] [Related]
3. Identification of miRNA-disease associations via deep forest ensemble learning based on autoencoder.
Liu W; Lin H; Huang L; Peng L; Tang T; Zhao Q; Yang L
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35325038
[TBL] [Abstract][Full Text] [Related]
4. DNRLMF-MDA:Predicting microRNA-Disease Associations Based on Similarities of microRNAs and Diseases.
Yan C; Wang J; Ni P; Lan W; Wu FX; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(1):233-243. PubMed ID: 29990253
[TBL] [Abstract][Full Text] [Related]
5. NEMPD: a network embedding-based method for predicting miRNA-disease associations by preserving behavior and attribute information.
Ji BY; You ZH; Chen ZH; Wong L; Yi HC
BMC Bioinformatics; 2020 Sep; 21(1):401. PubMed ID: 32912137
[TBL] [Abstract][Full Text] [Related]
6. SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder.
Wang S; Lin B; Zhang Y; Qiao S; Wang F; Wu W; Ren C
Cells; 2022 Dec; 11(24):. PubMed ID: 36552748
[TBL] [Abstract][Full Text] [Related]
7. A Computational Study of Potential miRNA-Disease Association Inference Based on Ensemble Learning and Kernel Ridge Regression.
Peng LH; Zhou LQ; Chen X; Piao X
Front Bioeng Biotechnol; 2020; 8():40. PubMed ID: 32117922
[TBL] [Abstract][Full Text] [Related]
8. SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost.
Liu D; Huang Y; Nie W; Zhang J; Deng L
BMC Bioinformatics; 2021 Apr; 22(1):219. PubMed ID: 33910505
[TBL] [Abstract][Full Text] [Related]
9. DBMDA: A Unified Embedding for Sequence-Based miRNA Similarity Measure with Applications to Predict and Validate miRNA-Disease Associations.
Zheng K; You ZH; Wang L; Zhou Y; Li LP; Li ZW
Mol Ther Nucleic Acids; 2020 Mar; 19():602-611. PubMed ID: 31931344
[TBL] [Abstract][Full Text] [Related]
10. Prioritizing CircRNA-Disease Associations With Convolutional Neural Network Based on Multiple Similarity Feature Fusion.
Fan C; Lei X; Pan Y
Front Genet; 2020; 11():540751. PubMed ID: 33193615
[TBL] [Abstract][Full Text] [Related]
11. Predicting miRNA-Disease Associations Through Deep Autoencoder With Multiple Kernel Learning.
Zhou F; Yin MM; Jiao CN; Zhao JX; Zheng CH; Liu JX
IEEE Trans Neural Netw Learn Syst; 2023 Sep; 34(9):5570-5579. PubMed ID: 34860656
[TBL] [Abstract][Full Text] [Related]
12. MLMDA: a machine learning approach to predict and validate MicroRNA-disease associations by integrating of heterogenous information sources.
Zheng K; You ZH; Wang L; Zhou Y; Li LP; Li ZW
J Transl Med; 2019 Aug; 17(1):260. PubMed ID: 31395072
[TBL] [Abstract][Full Text] [Related]
13. Novel Human miRNA-Disease Association Inference Based on Random Forest.
Chen X; Wang CC; Yin J; You ZH
Mol Ther Nucleic Acids; 2018 Dec; 13():568-579. PubMed ID: 30439645
[TBL] [Abstract][Full Text] [Related]
14. Prediction of miRNA-Disease Associations by Cascade Forest Model Based on Stacked Autoencoder.
Hu X; Yin Z; Zeng Z; Peng Y
Molecules; 2023 Jun; 28(13):. PubMed ID: 37446675
[TBL] [Abstract][Full Text] [Related]
15. IMPMD: An Integrated Method for Predicting Potential Associations Between miRNAs and Diseases.
Wu M; Yang Y; Wang H; Ding J; Zhu H; Xu Y
Curr Genomics; 2019 Dec; 20(8):581-591. PubMed ID: 32581646
[TBL] [Abstract][Full Text] [Related]
16. Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning.
Shen Y; Gao YL; Wang J; Guan BX; Liu JX
J Comput Biol; 2023 Aug; 30(8):926-936. PubMed ID: 37466461
[TBL] [Abstract][Full Text] [Related]
17. AEMDA: inferring miRNA-disease associations based on deep autoencoder.
Ji C; Gao Z; Ma X; Wu Q; Ni J; Zheng C
Bioinformatics; 2021 Apr; 37(1):66-72. PubMed ID: 32726399
[TBL] [Abstract][Full Text] [Related]
18. Improving miRNA Disease Association Prediction Accuracy Using Integrated Similarity Information and Deep Autoencoders.
S S; E R V; Krishnakumar U
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1125-1136. PubMed ID: 35914051
[TBL] [Abstract][Full Text] [Related]
19. A deep ensemble model to predict miRNA-disease association.
Fu L; Peng Q
Sci Rep; 2017 Nov; 7(1):14482. PubMed ID: 29101378
[TBL] [Abstract][Full Text] [Related]
20. A random forest based computational model for predicting novel lncRNA-disease associations.
Yao D; Zhan X; Zhan X; Kwoh CK; Li P; Wang J
BMC Bioinformatics; 2020 Mar; 21(1):126. PubMed ID: 32216744
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]