BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

320 related articles for article (PubMed ID: 35649392)

  • 1. RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins.
    Peng X; Wang X; Guo Y; Ge Z; Li F; Gao X; Song J
    Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35649392
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PreRBP-TL: prediction of species-specific RNA-binding proteins based on transfer learning.
    Zhang J; Yan K; Chen Q; Liu B
    Bioinformatics; 2022 Apr; 38(8):2135-2143. PubMed ID: 35176130
    [TBL] [Abstract][Full Text] [Related]  

  • 3. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.
    Pan X; Shen HB
    BMC Bioinformatics; 2017 Feb; 18(1):136. PubMed ID: 28245811
    [TBL] [Abstract][Full Text] [Related]  

  • 4. RNA-binding protein recognition based on multi-view deep feature and multi-label learning.
    Yang H; Deng Z; Pan X; Shen HB; Choi KS; Wang L; Wang S; Wu J
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32808039
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction.
    Su Y; Luo Y; Zhao X; Liu Y; Peng J
    PLoS Comput Biol; 2019 Sep; 15(9):e1007283. PubMed ID: 31483777
    [TBL] [Abstract][Full Text] [Related]  

  • 6. RBPLight: a computational tool for discovery of plant-specific RNA-binding proteins using light gradient boosting machine and ensemble of evolutionary features.
    Pradhan UK; Meher PK; Naha S; Pal S; Gupta S; Gupta A; Parsad R
    Brief Funct Genomics; 2023 Nov; 22(5):401-410. PubMed ID: 37158175
    [TBL] [Abstract][Full Text] [Related]  

  • 7. circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.
    Li H; Deng Z; Yang H; Pan X; Wei Z; Shen HB; Choi KS; Wang L; Wang S; Wu J
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34571539
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A deep learning framework for modeling structural features of RNA-binding protein targets.
    Zhang S; Zhou J; Hu H; Gong H; Chen L; Cheng C; Zeng J
    Nucleic Acids Res; 2016 Feb; 44(4):e32. PubMed ID: 26467480
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Recognizing binding sites of poorly characterized RNA-binding proteins on circular RNAs using attention Siamese network.
    Wu H; Pan X; Yang Y; Shen HB
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34297803
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Human protein-RNA interaction network is highly stable across mammals.
    Ramakrishnan A; Janga SC
    BMC Genomics; 2019 Dec; 20(Suppl 12):1004. PubMed ID: 31888461
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of Dynamic RBP-RNA Interactions Using PrismNet.
    Huang W; Zhang QC
    Methods Mol Biol; 2023; 2568():123-132. PubMed ID: 36227565
    [TBL] [Abstract][Full Text] [Related]  

  • 12. iDRBP_MMC: Identifying DNA-Binding Proteins and RNA-Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network.
    Zhang J; Chen Q; Liu B
    J Mol Biol; 2020 Nov; 432(22):5860-5875. PubMed ID: 32920048
    [TBL] [Abstract][Full Text] [Related]  

  • 13. CRIP: predicting circRNA-RBP-binding sites using a codon-based encoding and hybrid deep neural networks.
    Zhang K; Pan X; Yang Y; Shen HB
    RNA; 2019 Dec; 25(12):1604-1615. PubMed ID: 31537716
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. CRBPDL: Identification of circRNA-RBP interaction sites using an ensemble neural network approach.
    Niu M; Zou Q; Lin C
    PLoS Comput Biol; 2022 Jan; 18(1):e1009798. PubMed ID: 35051187
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of binding property of RNA-binding proteins using multi-sized filters and multi-modal deep convolutional neural network.
    Chung T; Kim D
    PLoS One; 2019; 14(4):e0216257. PubMed ID: 31026297
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of clustered RNA-binding protein motif sites in the mammalian genome.
    Zhang C; Lee KY; Swanson MS; Darnell RB
    Nucleic Acids Res; 2013 Aug; 41(14):6793-807. PubMed ID: 23685613
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.
    Li S; Dong F; Wu Y; Zhang S; Zhang C; Liu X; Jiang T; Zeng J
    Nucleic Acids Res; 2017 Aug; 45(14):e129. PubMed ID: 28575488
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning.
    Zheng J; Zhang X; Zhao X; Tong X; Hong X; Xie J; Liu S
    Sci Rep; 2018 Oct; 8(1):15264. PubMed ID: 30323214
    [TBL] [Abstract][Full Text] [Related]  

  • 20. In silico characterization and prediction of global protein-mRNA interactions in yeast.
    Pancaldi V; Bähler J
    Nucleic Acids Res; 2011 Aug; 39(14):5826-36. PubMed ID: 21459850
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.