| DiffusionST: A diffusion model-based framework for enhancing spatial transcriptomics data quality and identifying spatial domains Y Cui, Y Cui, R Wang, K Nakai, X Ye, T Sakurai, L Wei Available at SSRN 4894131, 0 | 2 | |
| HyGAnno: hybrid graph neural network–based cell type annotation for single-cell ATAC sequencing data W Zhang, Y Cui, B Liu, M Loza, SJ Park, K Nakai Briefings in Bioinformatics 25 (3), bbae152, 2024 | 1 | 2024 |
| STAIG: Spatial Transcriptomics Analysis via Image-Aided Graph Contrastive Learning for Domain Exploration and Alignment-Free Integration Y Yang, Y Cui, X Zeng, Y Zhang, M Loza, SJ Park, K Nakai bioRxiv, 2023.12. 18.572279, 2023 | 1 | 2023 |
| Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer Y Cui, W Zhang, X Zeng, Y Yang, SJ Park, K Nakai Frontiers in Immunology 15, 1497251, 2024 | | 2024 |
| Comparative single-cell transcriptomic analysis reveals putative differentiation drivers and potential origin of vertebrate retina X Zeng, F Gyoja, Y Cui, M Loza, TG Kusakabe, K Nakai NAR Genomics and Bioinformatics 6 (4), lqae149, 2024 | | 2024 |
| DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics Y Cui, R Wang, X Zeng, Y Cui, Z Zhu, K Nakai, X Ye, T Sakurai, L Wei bioRxiv, 2024.03. 04.583438, 2024 | | 2024 |
Kenta Nakaithe Institute of Medical Science, the University of Tokyo在 ims.u-tokyo.ac.jp 的电子邮件经过验证
Kenta Nakaithe Institute of Medical Science, the University of Tokyo在 ims.u-tokyo.ac.jp 的电子邮件经过验证