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 *

150 related articles for article (PubMed ID: 37759602)

  • 1. EpiMCI: Predicting Multi-Way Chromatin Interactions from Epigenomic Signals.
    Xu J; Zhang P; Sun W; Zhang J; Zhang W; Hou C; Li L
    Biology (Basel); 2023 Sep; 12(9):. PubMed ID: 37759602
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MATCHA: Probing multi-way chromatin interaction with hypergraph representation learning.
    Zhang R; Ma J
    Cell Syst; 2020 May; 10(5):397-407.e5. PubMed ID: 32550271
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Genetic sequence-based prediction of long-range chromatin interactions suggests a potential role of short tandem repeat sequences in genome organization.
    Nikumbh S; Pfeifer N
    BMC Bioinformatics; 2017 Apr; 18(1):218. PubMed ID: 28420341
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Understanding 3D Genome Organization and Its Effect on Transcriptional Gene Regulation Under Environmental Stress in Plant: A Chromatin Perspective.
    Kumar S; Kaur S; Seem K; Kumar S; Mohapatra T
    Front Cell Dev Biol; 2021; 9():774719. PubMed ID: 34957106
    [TBL] [Abstract][Full Text] [Related]  

  • 5. DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks.
    Liu T; Wang Z
    PLoS Comput Biol; 2023 Jul; 19(7):e1011307. PubMed ID: 37440599
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deciphering multi-way interactions in the human genome.
    Dotson GA; Chen C; Lindsly S; Cicalo A; Dilworth S; Ryan C; Jeyarajan S; Meixner W; Stansbury C; Pickard J; Beckloff N; Surana A; Wicha M; Muir LA; Rajapakse I
    Nat Commun; 2022 Sep; 13(1):5498. PubMed ID: 36127324
    [TBL] [Abstract][Full Text] [Related]  

  • 7. PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning.
    Deng Y; Zhang R; Xu P; Ma J; Gu Q
    bioRxiv; 2023 Oct; ():. PubMed ID: 37873233
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.
    Pancaldi V; Carrillo-de-Santa-Pau E; Javierre BM; Juan D; Fraser P; Spivakov M; Valencia A; Rico D
    Genome Biol; 2016 Jul; 17(1):152. PubMed ID: 27391817
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Exploring complex and heterogeneous correlations on hypergraph for the prediction of drug-target interactions.
    Ruan D; Ji S; Yan C; Zhu J; Zhao X; Yang Y; Gao Y; Zou C; Dai Q
    Patterns (N Y); 2021 Dec; 2(12):100390. PubMed ID: 34950907
    [TBL] [Abstract][Full Text] [Related]  

  • 10. High-throughput Pore-C reveals the single-allele topology and cell type-specificity of 3D genome folding.
    Zhong JY; Niu L; Lin ZB; Bai X; Chen Y; Luo F; Hou C; Xiao CL
    Nat Commun; 2023 Mar; 14(1):1250. PubMed ID: 36878904
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Does multi-way, long-range chromatin contact data advance 3D genome reconstruction?
    Olshen AB; Segal MR
    BMC Bioinformatics; 2023 Feb; 24(1):64. PubMed ID: 36829114
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multiscale and integrative single-cell Hi-C analysis with Higashi.
    Zhang R; Zhou T; Ma J
    Nat Biotechnol; 2022 Feb; 40(2):254-261. PubMed ID: 34635838
    [TBL] [Abstract][Full Text] [Related]  

  • 13. MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification.
    Tian SZ; Li G; Ning D; Jing K; Xu Y; Yang Y; Fullwood MJ; Yin P; Huang G; Plewczynski D; Zhai J; Dai Z; Chen W; Zheng M
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36094071
    [TBL] [Abstract][Full Text] [Related]  

  • 14. HGNN
    Gao Y; Feng Y; Ji S; Ji R
    IEEE Trans Pattern Anal Mach Intell; 2023 Mar; 45(3):3181-3199. PubMed ID: 35696461
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.
    Tao H; Li H; Xu K; Hong H; Jiang S; Du G; Wang J; Sun Y; Huang X; Ding Y; Li F; Zheng X; Chen H; Bo X
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33454752
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.
    Vanhaeren T; Divina F; García-Torres M; Gómez-Vela F; Vanhoof W; Martínez-García PM
    Genes (Basel); 2020 Aug; 11(9):. PubMed ID: 32847102
    [TBL] [Abstract][Full Text] [Related]  

  • 17. HiCNN: a very deep convolutional neural network to better enhance the resolution of Hi-C data.
    Liu T; Wang Z
    Bioinformatics; 2019 Nov; 35(21):4222-4228. PubMed ID: 31056636
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Assessing relationships between chromatin interactions and regulatory genomic activities using the self-organizing map.
    Kunz T; Rieber L; Mahony S
    Methods; 2021 May; 189():12-21. PubMed ID: 32652235
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting chromatin organization using histone marks.
    Huang J; Marco E; Pinello L; Yuan GC
    Genome Biol; 2015 Aug; 16(1):162. PubMed ID: 26272203
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Two main stream methods analysis and visual 3D genome architecture.
    Fu S; Zhang L; Lv J; Zhu B; Wang W; Wang X
    Semin Cell Dev Biol; 2019 Jun; 90():43-53. PubMed ID: 30059749
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.