BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

119 related articles for article (PubMed ID: 37920888)

  • 21. MVGCN: data integration through multi-view graph convolutional network for predicting links in biomedical bipartite networks.
    Fu H; Huang F; Liu X; Qiu Y; Zhang W
    Bioinformatics; 2022 Jan; 38(2):426-434. PubMed ID: 34499148
    [TBL] [Abstract][Full Text] [Related]  

  • 22. KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations.
    Wu J; Ning Z; Ding Y; Wang Y; Peng Q; Fu L
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37587836
    [TBL] [Abstract][Full Text] [Related]  

  • 23. LION: an integrated R package for effective prediction of ncRNA-protein interaction.
    Han S; Yang X; Sun H; Yang H; Zhang Q; Peng C; Fang W; Li Y
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36155620
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases.
    Sheng N; Wang Y; Huang L; Gao L; Cao Y; Xie X; Fu Y
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37529914
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning.
    Fang SG; Huang D; Cai XS; Wang CD; He C; Tang Y
    IEEE Trans Neural Netw Learn Syst; 2023 Apr; PP():. PubMed ID: 37030820
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks.
    Ma Y; Zhang H; Jin C; Kang C
    Front Genet; 2023; 14():1136672. PubMed ID: 36845380
    [No Abstract]   [Full Text] [Related]  

  • 27. Multiphysical graph neural network (MP-GNN) for COVID-19 drug design.
    Li XS; Liu X; Lu L; Hua XS; Chi Y; Xia K
    Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35696650
    [TBL] [Abstract][Full Text] [Related]  

  • 28. IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction.
    Pan X; Fan YX; Yan J; Shen HB
    BMC Genomics; 2016 Aug; 17():582. PubMed ID: 27506469
    [TBL] [Abstract][Full Text] [Related]  

  • 29. GraphTGI: an attention-based graph embedding model for predicting TF-target gene interactions.
    Du ZH; Wu YH; Huang YA; Chen J; Pan GQ; Hu L; You ZH; Li JQ
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35511108
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations.
    Shi Z; Zhang H; Jin C; Quan X; Yin Y
    BMC Bioinformatics; 2021 Mar; 22(1):136. PubMed ID: 33745450
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Heterogeneous graph inference based on similarity network fusion for predicting lncRNA-miRNA interaction.
    Fan Y; Cui J; Zhu Q
    RSC Adv; 2020 Mar; 10(20):11634-11642. PubMed ID: 35496629
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Identify ncRNA Subcellular Localization via Graph Regularized k-Local Hyperplane Distance Nearest Neighbor Model on Multi-Kernel Learning.
    Zhou H; Wang H; Tang J; Ding Y; Guo F
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3517-3529. PubMed ID: 34432632
    [TBL] [Abstract][Full Text] [Related]  

  • 33. MS-BACL: enhancing metabolic stability prediction through bond graph augmentation and contrastive learning.
    Wang T; Li Z; Zhuo L; Chen Y; Fu X; Zou Q
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38555479
    [TBL] [Abstract][Full Text] [Related]  

  • 34. DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science.
    Li M; Zhou J; Hu J; Fan W; Zhang Y; Gu Y; Karypis G
    ACS Omega; 2021 Oct; 6(41):27233-27238. PubMed ID: 34693143
    [TBL] [Abstract][Full Text] [Related]  

  • 35. DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding.
    Zeng M; Wu Y; Lu C; Zhang F; Wu FX; Li M
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34498677
    [TBL] [Abstract][Full Text] [Related]  

  • 36. GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning.
    Wei J; Zhuo L; Zhou Z; Lian X; Fu X; Yao X
    Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37427977
    [TBL] [Abstract][Full Text] [Related]  

  • 37. BGFE: A Deep Learning Model for ncRNA-Protein Interaction Predictions Based on Improved Sequence Information.
    Zhan ZH; Jia LN; Zhou Y; Li LP; Yi HC
    Int J Mol Sci; 2019 Feb; 20(4):. PubMed ID: 30813451
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs.
    Xuan P; Wang S; Cui H; Zhao Y; Zhang T; Wu P
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36088549
    [TBL] [Abstract][Full Text] [Related]  

  • 39. NPInter v4.0: an integrated database of ncRNA interactions.
    Teng X; Chen X; Xue H; Tang Y; Zhang P; Kang Q; Hao Y; Chen R; Zhao Y; He S
    Nucleic Acids Res; 2020 Jan; 48(D1):D160-D165. PubMed ID: 31670377
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A computational model of circRNA-associated diseases based on a graph neural network: prediction and case studies for follow-up experimental validation.
    Niu M; Wang C; Zhang Z; Zou Q
    BMC Biol; 2024 Jan; 22(1):24. PubMed ID: 38281919
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.