BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

182 related articles for article (PubMed ID: 38553698)

  • 1. DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation.
    Liu Y; Zhang R; Dong X; Yang H; Li J; Cao H; Tian J; Zhang Y
    BMC Bioinformatics; 2024 Mar; 25(1):139. PubMed ID: 38553698
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 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. DAESTB: inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder.
    Peng L; Tu Y; Huang L; Li Y; Fu X; Chen X
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36377749
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.
    Xuan P; Sun H; Wang X; Zhang T; Pan S
    Int J Mol Sci; 2019 Jul; 20(15):. PubMed ID: 31349729
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features.
    Guo Y; Zhou D; Ruan X; Cao J
    Neural Netw; 2023 Aug; 165():491-505. PubMed ID: 37336034
    [TBL] [Abstract][Full Text] [Related]  

  • 9. LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier.
    Lu C; Xie M
    Interdiscip Sci; 2023 Sep; 15(3):439-451. PubMed ID: 37308797
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction of potential miRNA-disease associations based on stacked autoencoder.
    Wang CC; Li TH; Huang L; Chen X
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35176761
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. PDMDA: predicting deep-level miRNA-disease associations with graph neural networks and sequence features.
    Yan C; Duan G; Li N; Zhang L; Wu FX; Wang J
    Bioinformatics; 2022 Apr; 38(8):2226-2234. PubMed ID: 35150255
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Semi-Supervised Learning Method for MiRNA-Disease Association Prediction Based on Variational Autoencoder.
    Ji C; Wang Y; Gao Z; Li L; Ni J; Zheng C
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2049-2059. PubMed ID: 33735084
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A structural deep network embedding model for predicting associations between miRNA and disease based on molecular association network.
    Li HY; Chen HY; Wang L; Song SJ; You ZH; Yan X; Yu JQ
    Sci Rep; 2021 Jun; 11(1):12640. PubMed ID: 34135401
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations.
    Guo LX; Wang L; You ZH; Yu CQ; Hu ML; Zhao BW; Li Y
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38324624
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Prediction of Disease-related microRNAs through Integrating Attributes of microRNA Nodes and Multiple Kinds of Connecting Edges.
    Xuan P; Li L; Zhang T; Zhang Y; Song Y
    Molecules; 2019 Aug; 24(17):. PubMed ID: 31455026
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Dual-Network Collaborative Matrix Factorization for predicting small molecule-miRNA associations.
    Wang SH; Wang CC; Huang L; Miao LY; Chen X
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34864865
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.