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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

183 related articles for article (PubMed ID: 38507691)

  • 21. DEAttentionDTA: protein-ligand binding affinity prediction based on dynamic embedding and self-attention.
    Chen X; Huang J; Shen T; Zhang H; Xu L; Yang M; Xie X; Yan Y; Yan J
    Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38897656
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Improved compound-protein interaction site and binding affinity prediction using self-supervised protein embeddings.
    Wu J; Liu Z; Yang X; Lin Z
    BMC Bioinformatics; 2022 Dec; 23(1):543. PubMed ID: 36526969
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks.
    Pan X; Rijnbeek P; Yan J; Shen HB
    BMC Genomics; 2018 Jul; 19(1):511. PubMed ID: 29970003
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.
    Pan X; Shen HB
    Bioinformatics; 2018 Oct; 34(20):3427-3436. PubMed ID: 29722865
    [TBL] [Abstract][Full Text] [Related]  

  • 25. DataDTA: a multi-feature and dual-interaction aggregation framework for drug-target binding affinity prediction.
    Zhu Y; Zhao L; Wen N; Wang J; Wang C
    Bioinformatics; 2023 Sep; 39(9):. PubMed ID: 37688568
    [TBL] [Abstract][Full Text] [Related]  

  • 26. A deep neural network approach for learning intrinsic protein-RNA binding preferences.
    Ben-Bassat I; Chor B; Orenstein Y
    Bioinformatics; 2018 Sep; 34(17):i638-i646. PubMed ID: 30423078
    [TBL] [Abstract][Full Text] [Related]  

  • 27. DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites.
    Zhang J; Liu B; Wang Z; Lehnert K; Gahegan M
    BMC Bioinformatics; 2022 Jun; 23(1):257. PubMed ID: 35768792
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Learning long- and short-term dependencies for improving drug-target binding affinity prediction using transformer and edge contraction pooling.
    Gao M; Jiang S; Ding W; Xu T; Lyu Z
    J Bioinform Comput Biol; 2024 Feb; 22(1):2350030. PubMed ID: 38567388
    [TBL] [Abstract][Full Text] [Related]  

  • 29. CRMSNet: A deep learning model that uses convolution and residual multi-head self-attention block to predict RBPs for RNA sequence.
    Pan Z; Zhou S; Zou H; Liu C; Zang M; Liu T; Wang Q
    Proteins; 2023 Aug; 91(8):1032-1041. PubMed ID: 36935548
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Predicting protein-ligand binding residues with deep convolutional neural networks.
    Cui Y; Dong Q; Hong D; Wang X
    BMC Bioinformatics; 2019 Feb; 20(1):93. PubMed ID: 30808287
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Sfcnn: a novel scoring function based on 3D convolutional neural network for accurate and stable protein-ligand affinity prediction.
    Wang Y; Wei Z; Xi L
    BMC Bioinformatics; 2022 Jun; 23(1):222. PubMed ID: 35676617
    [TBL] [Abstract][Full Text] [Related]  

  • 32. AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.
    Kwon Y; Shin WH; Ko J; Lee J
    Int J Mol Sci; 2020 Nov; 21(22):. PubMed ID: 33182567
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Ligand binding affinity prediction with fusion of graph neural networks and 3D structure-based complex graph.
    Dong L; Shi S; Qu X; Luo D; Wang B
    Phys Chem Chem Phys; 2023 Sep; 25(35):24110-24120. PubMed ID: 37655493
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Predicting drug-target binding affinity with cross-scale graph contrastive learning.
    Wang J; Xiao Y; Shang X; Peng J
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38221904
    [TBL] [Abstract][Full Text] [Related]  

  • 35. DeepNC: a framework for drug-target interaction prediction with graph neural networks.
    Tran HNT; Thomas JJ; Ahamed Hassain Malim NH
    PeerJ; 2022; 10():e13163. PubMed ID: 35578674
    [TBL] [Abstract][Full Text] [Related]  

  • 36. 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]  

  • 37. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation.
    Chaitanya K; Erdil E; Karani N; Konukoglu E
    Med Image Anal; 2023 Jul; 87():102792. PubMed ID: 37054649
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.
    Jones D; Kim H; Zhang X; Zemla A; Stevenson G; Bennett WFD; Kirshner D; Wong SE; Lightstone FC; Allen JE
    J Chem Inf Model; 2021 Apr; 61(4):1583-1592. PubMed ID: 33754707
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Attention-aware 3D U-Net convolutional neural network for knowledge-based planning 3D dose distribution prediction of head-and-neck cancer.
    Osman AFI; Tamam NM
    J Appl Clin Med Phys; 2022 Jul; 23(7):e13630. PubMed ID: 35533234
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Graph Convolutional Network and Contrastive Learning Small Nucleolar RNA (snoRNA) Disease Associations (GCLSDA): Predicting snoRNA-Disease Associations via Graph Convolutional Network and Contrastive Learning.
    Zhang L; Chen M; Hu X; Deng L
    Int J Mol Sci; 2023 Sep; 24(19):. PubMed ID: 37833876
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.