312 related articles for article (PubMed ID: 38678389)
1. scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.
Zhai Y; Chen L; Deng M
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38678389
[TBL] [Abstract][Full Text] [Related]
2. scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery.
Zhai Y; Chen L; Deng M
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36869836
[TBL] [Abstract][Full Text] [Related]
3. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.
Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X
Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596
[TBL] [Abstract][Full Text] [Related]
4. STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering.
Peng L; He X; Peng X; Li Z; Zhang L
Comput Biol Med; 2023 Nov; 166():107440. PubMed ID: 37738898
[TBL] [Abstract][Full Text] [Related]
5. Computational solutions for spatial transcriptomics.
Kleino I; Frolovaitė P; Suomi T; Elo LL
Comput Struct Biotechnol J; 2022; 20():4870-4884. PubMed ID: 36147664
[TBL] [Abstract][Full Text] [Related]
6. scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data.
Zhai Y; Chen L; Deng M
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38366803
[TBL] [Abstract][Full Text] [Related]
7. SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data.
Yuan M; Wan H; Wang Z; Guo Q; Deng M
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38279647
[TBL] [Abstract][Full Text] [Related]
8. Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis.
Geddes TA; Kim T; Nan L; Burchfield JG; Yang JYH; Tao D; Yang P
BMC Bioinformatics; 2019 Dec; 20(Suppl 19):660. PubMed ID: 31870278
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data.
Wan H; Yuan M; Fu Y; Deng M
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38388681
[TBL] [Abstract][Full Text] [Related]
11. stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.
Shengquan C; Boheng Z; Xiaoyang C; Xuegong Z; Rui J
Bioinformatics; 2021 Jul; 37(Suppl_1):i299-i307. PubMed ID: 34252941
[TBL] [Abstract][Full Text] [Related]
12. Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep.
Liu T; Fang Z; Li X; Zhang L; Cao DS; Li M; Yin M
Bioinformatics; 2024 Jan; 40(1):. PubMed ID: 38243703
[TBL] [Abstract][Full Text] [Related]
13. stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics.
Fang Z; Liu T; Zheng R; A J; Yin M; Li M
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38189544
[TBL] [Abstract][Full Text] [Related]
14. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
15. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
Srinivasan S; Leshchyk A; Johnson NT; Korkin D
RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
[TBL] [Abstract][Full Text] [Related]
16. Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.
Gan Y; Huang X; Zou G; Zhou S; Guan J
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35172334
[TBL] [Abstract][Full Text] [Related]
17. Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptation.
Chen L; He Q; Zhai Y; Deng M
Bioinformatics; 2021 May; 37(6):775-784. PubMed ID: 33098418
[TBL] [Abstract][Full Text] [Related]
18. scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets.
Yuan M; Chen L; Deng M
Bioinformatics; 2022 Jan; 38(3):738-745. PubMed ID: 34623390
[TBL] [Abstract][Full Text] [Related]
19. Learning deep features and topological structure of cells for clustering of scRNA-sequencing data.
Wang H; Ma X
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35302164
[TBL] [Abstract][Full Text] [Related]
20. Deep enhanced constraint clustering based on contrastive learning for scRNA-seq data.
Gan Y; Chen Y; Xu G; Guo W; Zou G
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37313714
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
