207 related articles for article (PubMed ID: 36168811)
1. dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using time-course single-cell gene expression data.
Xu Y; Chen J; Lyu A; Cheung WK; Zhang L
Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36168811
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data.
Chen G; Liu ZP
Bioinformatics; 2022 Sep; 38(19):4522-4529. PubMed ID: 35961023
[TBL] [Abstract][Full Text] [Related]
4. 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]
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. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network.
Huang Z; Wang J; Lu X; Mohd Zain A; Yu G
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36733262
[TBL] [Abstract][Full Text] [Related]
7. STGRNS: an interpretable transformer-based method for inferring gene regulatory networks from single-cell transcriptomic data.
Xu J; Zhang A; Liu F; Zhang X
Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 37004161
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.
Brendel M; Su C; Bai Z; Zhang H; Elemento O; Wang F
Genomics Proteomics Bioinformatics; 2022 Oct; 20(5):814-835. PubMed ID: 36528240
[TBL] [Abstract][Full Text] [Related]
10. MLSpatial: A machine-learning method to reconstruct the spatial distribution of cells from scRNA-seq by extracting spatial features.
Zhu M; Li C; Lv K; Guo H; Hou R; Tian G; Yang J
Comput Biol Med; 2023 Jun; 159():106873. PubMed ID: 37105115
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Joint gene network construction by single-cell RNA sequencing data.
Dong M; He Y; Jiang Y; Zou F
Biometrics; 2023 Jun; 79(2):915-925. PubMed ID: 35184277
[TBL] [Abstract][Full Text] [Related]
13. Inferring gene regulatory networks from single-cell transcriptomics based on graph embedding.
Gan Y; Yu J; Xu G; Yan C; Zou G
Bioinformatics; 2024 May; 40(5):. PubMed ID: 38810116
[TBL] [Abstract][Full Text] [Related]
14. Single-cell multi-omics analysis identifies context-specific gene regulatory gates and mechanisms.
Malekpour SA; Haghverdi L; Sadeghi M
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38653489
[TBL] [Abstract][Full Text] [Related]
15. BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes.
Wang T; Johnson TS; Shao W; Lu Z; Helm BR; Zhang J; Huang K
Genome Biol; 2019 Aug; 20(1):165. PubMed ID: 31405383
[TBL] [Abstract][Full Text] [Related]
16. MICRAT: a novel algorithm for inferring gene regulatory networks using time series gene expression data.
Yang B; Xu Y; Maxwell A; Koh W; Gong P; Zhang C
BMC Syst Biol; 2018 Dec; 12(Suppl 7):115. PubMed ID: 30547796
[TBL] [Abstract][Full Text] [Related]
17. A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.
Lakkis J; Wang D; Zhang Y; Hu G; Wang K; Pan H; Ungar L; Reilly MP; Li X; Li M
Genome Res; 2021 Oct; 31(10):1753-1766. PubMed ID: 34035047
[TBL] [Abstract][Full Text] [Related]
18. Deep learning-based advances and applications for single-cell RNA-sequencing data analysis.
Bao S; Li K; Yan C; Zhang Z; Qu J; Zhou M
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34849562
[TBL] [Abstract][Full Text] [Related]
19. Graph embedding and Gaussian mixture variational autoencoder network for end-to-end analysis of single-cell RNA sequencing data.
Xu J; Xu J; Meng Y; Lu C; Cai L; Zeng X; Nussinov R; Cheng F
Cell Rep Methods; 2023 Jan; 3(1):100382. PubMed ID: 36814845
[TBL] [Abstract][Full Text] [Related]
20. Gene Regulatory Network Inference Using Convolutional Neural Networks from scRNA-seq Data.
Mao G; Pang Z; Zuo K; Liu J
J Comput Biol; 2023 May; 30(5):619-631. PubMed ID: 36877552
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]