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 *

237 related articles for article (PubMed ID: 35050715)

  • 1. GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks.
    Shrivastava H; Zhang X; Song L; Aluru S
    J Comput Biol; 2022 Jan; 29(1):27-44. PubMed ID: 35050715
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations.
    Lei Y; Huang XT; Guo X; Hang Katie Chan K; Gao L
    Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38980373
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network.
    Wang Y; Zhou F; Guan J
    Bioinformatics; 2024 Jul; 40(7):. PubMed ID: 38950180
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data.
    Chen J; Cheong C; Lan L; Zhou X; Liu J; Lyu A; Cheung WK; Zhang L
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34424948
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks.
    Mao G; Pang Z; Zuo K; Wang Q; Pei X; Chen X; Liu J
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37985457
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and Annotation.
    Chen L; Zhai Y; He Q; Wang W; Deng M
    Genes (Basel); 2020 Jul; 11(7):. PubMed ID: 32674393
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning of gene relationships from single cell time-course expression data.
    Yuan Y; Bar-Joseph Z
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33876191
    [TBL] [Abstract][Full Text] [Related]  

  • 8. DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data.
    Zhou X; Pan J; Chen L; Zhang S; Chen Y
    Biomolecules; 2024 Jun; 14(7):. PubMed ID: 39062480
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Reconstructing Genetic Regulatory Networks Using Two-Step Algorithms with the Differential Equation Models of Neural Networks.
    Chen CK
    Interdiscip Sci; 2018 Dec; 10(4):823-835. PubMed ID: 28748400
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data.
    Razaghi-Moghadam Z; Nikoloski Z
    NPJ Syst Biol Appl; 2020 Jun; 6(1):21. PubMed ID: 32606380
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Inference of Gene Regulatory Networks Based on Multi-view Hierarchical Hypergraphs.
    Wu S; Jin K; Tang M; Xia Y; Gao W
    Interdiscip Sci; 2024 Jun; 16(2):318-332. PubMed ID: 38342857
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A hybrid deep learning framework for gene regulatory network inference from single-cell transcriptomic data.
    Zhao M; He W; Tang J; Zou Q; Guo F
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35062026
    [TBL] [Abstract][Full Text] [Related]  

  • 13. scTIGER: A Deep-Learning Method for Inferring Gene Regulatory Networks from Case versus Control scRNA-seq Datasets.
    Dautle M; Zhang S; Chen Y
    Int J Mol Sci; 2023 Aug; 24(17):. PubMed ID: 37686146
    [TBL] [Abstract][Full Text] [Related]  

  • 14. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks.
    Zinati Y; Takiddeen A; Emad A
    Nat Commun; 2024 May; 15(1):4055. PubMed ID: 38744843
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions.
    Shojaee A; Huang SC
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37897702
    [TBL] [Abstract][Full Text] [Related]  

  • 16. SIGNET: single-cell RNA-seq-based gene regulatory network prediction using multiple-layer perceptron bagging.
    Luo Q; Yu Y; Lan X
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34962260
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A gene regulatory network inference model based on pseudo-siamese network.
    Wang Q; Guo M; Chen J; Duan R
    BMC Bioinformatics; 2023 Apr; 24(1):163. PubMed ID: 37085776
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Inferring gene regulatory networks from single-cell gene expression data via deep multi-view contrastive learning.
    Lin Z; Ou-Yang L
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36585783
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-supervised prediction of gene regulatory networks using machine learning algorithms.
    Patel N; Wang JT
    J Biosci; 2015 Oct; 40(4):731-40. PubMed ID: 26564975
    [TBL] [Abstract][Full Text] [Related]  

  • 20. SCMAG: A Semisupervised Single-Cell Clustering Method Based on Matrix Aggregation Graph Convolutional Neural Network.
    Peng H; Fan W; Fang C; Gao W; Li Y
    Comput Math Methods Med; 2021; 2021():6842752. PubMed ID: 34646337
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.