BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

131 related articles for article (PubMed ID: 31410461)

  • 1. EPIP: a novel approach for condition-specific enhancer-promoter interaction prediction.
    Talukder A; Saadat S; Li X; Hu H
    Bioinformatics; 2019 Oct; 35(20):3877-3883. PubMed ID: 31410461
    [TBL] [Abstract][Full Text] [Related]  

  • 2. EPI-Mind: Identifying Enhancer-Promoter Interactions Based on Transformer Mechanism.
    Ni Y; Fan L; Wang M; Zhang N; Zuo Y; Liao M
    Interdiscip Sci; 2022 Sep; 14(3):786-794. PubMed ID: 35633468
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of enhancer-promoter interactions using the cross-cell type information and domain adversarial neural network.
    Jing F; Zhang SW; Zhang S
    BMC Bioinformatics; 2020 Nov; 21(1):507. PubMed ID: 33160328
    [TBL] [Abstract][Full Text] [Related]  

  • 4. EPIHC: Improving Enhancer-Promoter Interaction Prediction by Using Hybrid Features and Communicative Learning.
    Liu S; Xu X; Yang Z; Zhao X; Liu S; Zhang W
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3435-3443. PubMed ID: 34473626
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.
    Zeng W; Wang Y; Jiang R
    Bioinformatics; 2020 Jan; 36(2):496-503. PubMed ID: 31318408
    [TBL] [Abstract][Full Text] [Related]  

  • 6. StackEPI: identification of cell line-specific enhancer-promoter interactions based on stacking ensemble learning.
    Fan Y; Peng B
    BMC Bioinformatics; 2022 Jul; 23(1):272. PubMed ID: 35820811
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A simple convolutional neural network for prediction of enhancer-promoter interactions with DNA sequence data.
    Zhuang Z; Shen X; Pan W
    Bioinformatics; 2019 Sep; 35(17):2899-2906. PubMed ID: 30649185
    [TBL] [Abstract][Full Text] [Related]  

  • 8. TarPmiR: a new approach for microRNA target site prediction.
    Ding J; Li X; Hu H
    Bioinformatics; 2016 Sep; 32(18):2768-75. PubMed ID: 27207945
    [TBL] [Abstract][Full Text] [Related]  

  • 9. EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction.
    Ahmed FS; Aly S; Liu X
    BMC Bioinformatics; 2024 Jun; 25(1):216. PubMed ID: 38890584
    [TBL] [Abstract][Full Text] [Related]  

  • 10. PETModule: a motif module based approach for enhancer target gene prediction.
    Zhao C; Li X; Hu H
    Sci Rep; 2016 Jul; 6():30043. PubMed ID: 27436110
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Recognition of long-range enhancer-promoter interactions by adding genomic signatures of segmented regulatory regions.
    Feng ZX; Li QZ
    Genomics; 2017 Oct; 109(5-6):341-352. PubMed ID: 28579514
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Delta.EPI: a probabilistic voting-based enhancer-promoter interaction prediction platform.
    Zhang Y; Wang H; Liu J; Li J; Zhang Q; Tang B; Zhang Z
    J Genet Genomics; 2023 Jul; 50(7):519-527. PubMed ID: 36822264
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of enhancer-promoter interactions via natural language processing.
    Zeng W; Wu M; Jiang R
    BMC Genomics; 2018 May; 19(Suppl 2):84. PubMed ID: 29764360
    [TBL] [Abstract][Full Text] [Related]  

  • 14. BHap: a novel approach for bacterial haplotype reconstruction.
    Li X; Saadat S; Hu H; Li X
    Bioinformatics; 2019 Nov; 35(22):4624-4631. PubMed ID: 31004480
    [TBL] [Abstract][Full Text] [Related]  

  • 15. DeepPHiC: predicting promoter-centered chromatin interactions using a novel deep learning approach.
    Agarwal A; Chen L
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36495179
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction.
    Min X; Lu F; Li C
    Curr Pharm Des; 2021; 27(15):1847-1855. PubMed ID: 33234095
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identifying enhancer-promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism.
    Hong Z; Zeng X; Wei L; Liu X
    Bioinformatics; 2020 Feb; 36(4):1037-1043. PubMed ID: 31588505
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Exploiting sequence-based features for predicting enhancer-promoter interactions.
    Yang Y; Zhang R; Singh S; Ma J
    Bioinformatics; 2017 Jul; 33(14):i252-i260. PubMed ID: 28881991
    [TBL] [Abstract][Full Text] [Related]  

  • 19. EPIsHilbert: Prediction of Enhancer-Promoter Interactions via Hilbert Curve Encoding and Transfer Learning.
    Zhang M; Hu Y; Zhu M
    Genes (Basel); 2021 Sep; 12(9):. PubMed ID: 34573367
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Predicting enhancer-promoter interaction based on epigenomic signals.
    Zheng L; Liu L; Zhu W; Ding Y; Wu F
    Front Genet; 2023; 14():1133775. PubMed ID: 37144127
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 7.