| Machine Learning for Synthetic Data Generation: a Review Y Lu, M Shen, H Wang, C van Rechem, W Wei arXiv preprint arXiv:2302.04062, 2023 | 86 | 2023 |
| Comparative assessment and novel strategy on methods for imputing proteomics data M Shen, YT Chang, CT Wu, SJ Parker, G Saylor, Y Wang, G Yu, ... Scientific reports 12 (1), 1067, 2022 | 17 | 2022 |
| Cosbin: cosine score-based iterative normalization of biologically diverse samples CT Wu, M Shen, D Du, Z Cheng, SJ Parker, Y Lu, JE Van Eyk, G Yu, ... Bioinformatics Advances 2 (1), vbac076, 2022 | 7 | 2022 |
| Machine Learning for Synthetic Data Generation: A Review. arXiv Y Lu, M Shen, H Wang, W Wei arXiv preprint arXiv:2302.04062, 2023 | 6 | 2023 |
| Comparative Assessment and Outlook on Methods for Imputing Proteomics Data M Shen, YT Chang, CT Wu, SJ Parker, G Saylor, Y Wang, G Yu, ... | 2 | 2021 |
| Determining molecular archetype composition and expression from bulk tissues with unsupervised deconvolution CT Wu, L Chen, DM Herrington, M Shen, G Yu, R Clarke, C Liu, Y Wang bioRxiv, 2021.07. 12.452047, 2021 | 1 | 2021 |
| GenoCraft: A Comprehensive, User-Friendly Web-Based Platform for High-Throughput Omics Data Analysis and Visualization Y Lu, M Shen, Y Zhao, C Li, F Meng, X Wang, D Herrington, Y Wang, T Fu, ... arXiv preprint arXiv:2312.14249, 2023 | | 2023 |
| A Study of Machine Learning Approaches for Biomedical Signal Processing M Shen Virginia Tech, 2021 | | 2021 |
Yingzhou LuStanford University在 Stanford.edu 的电子邮件经过验证
Yingzhou LuStanford University在 Stanford.edu 的电子邮件经过验证