| Deep learning for inferring gene relationships from single-cell expression data Y Yuan, Z Bar-Joseph Proceedings of the National Academy of Sciences 116 (52), 27151-27158, 2019 | 163 | 2019 |
| GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data Y Yuan, Z Bar-Joseph Genome biology 21, 1-16, 2020 | 122 | 2020 |
| Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit Y Yuan, B Liu, P Xie, MQ Zhang, Y Li, Z Xie, X Wang Proceedings of the National Academy of Sciences 112 (10), 3158-3163, 2015 | 101 | 2015 |
| Cell clustering for spatial transcriptomics data with graph neural networks J Li, S Chen, X Pan, Y Yuan, HB Shen Nature Computational Science 2 (6), 399-408, 2022 | 71 | 2022 |
| Clustering spatial transcriptomics data H Teng, Y Yuan, Z Bar-Joseph Bioinformatics 38 (4), 997-1004, 2022 | 34* | 2022 |
| Regulation by competition: a hidden layer of gene regulatory network L Wei, Y Yuan, T Hu, S Li, T Cheng, J Lei, Z Xie, MQ Zhang, X Wang Quantitative Biology 7 (2), 110-121, 2019 | 24 | 2019 |
| Regulation by competition: a hidden layer of gene regulatory network L Wei, Y Yuan, T Hu, S Li, T Cheng, J Lei, Z Xie, MQ Zhang, X Wang Quantitative Biology 7 (2), 110-121, 2019 | 24 | 2019 |
| Identification of genes associated with the impairment of olfactory and gustatory functions in COVID-19 via machine-learning methods J Ren, Y Zhang, W Guo, K Feng, Y Yuan, T Huang, YD Cai Life 13 (3), 798, 2023 | 20 | 2023 |
| Advances in spatial transcriptomics and related data analysis strategies J Du, YC Yang, ZJ An, MH Zhang, XH Fu, ZF Huang, Y Yuan, J Hou Journal of Translational Medicine 21 (1), 330, 2023 | 19 | 2023 |
| Information, awareness, and mental health: Evidence from air pollution disclosure in China T Xie, Y Yuan, H Zhang Journal of Environmental Economics and Management 120, 102827, 2023 | 16 | 2023 |
| Deep learning of gene relationships from single cell time-course expression data Y Yuan, Z Bar-Joseph Briefings in bioinformatics 22 (5), bbab142, 2021 | 16 | 2021 |
| A quantitative understanding of microRNA-mediated competing endogenous RNA regulation Y Yuan, X Ren, Z Xie, X Wang Quantitative Biology 4, 47-57, 2016 | 15 | 2016 |
| Go with the wind: Spatial impacts of environmental regulations on economic activities in China T Xie, Y Yuan Journal of Development Economics 164, 103139, 2023 | 11 | 2023 |
| The consequences of health shocks on households: Evidence from China Y Wang, Z Jin, Y Yuan China Economic Review 79, 101969, 2023 | 7 | 2023 |
| CINS: Cell Interaction Network inference from Single cell expression data Y Yuan, C Cosme Jr, TS Adams, J Schupp, K Sakamoto, N Xylourgidis, ... PLOS Computational Biology 18 (9), e1010468, 2022 | 7 | 2022 |
| Air pollution kills competition: Evidence from eSports J Mo, Z Wu, Y Yuan Journal of Environmental Economics and Management 122, 102886, 2023 | 3 | 2023 |
| Causal inference using deep neural networks Y Yuan, X Ding, Z Bar-Joseph arXiv preprint arXiv:2011.12508, 2020 | 3 | 2020 |
| DG-Affinity: predicting antigen–antibody affinity with language models from sequences Y Yuan, Q Chen, J Mao, G Li, X Pan BMC bioinformatics 24 (1), 430, 2023 | 2 | 2023 |
| Cost-effectiveness of medical migration for chronic kidney disease: a national cross-sectional study in China Y Ao, C Yang, P Li, F Wang, S Peng, HY Wang, J Wang, MH Zhao, ... BMC Health Services Research 22 (1), 912, 2022 | 2 | 2022 |
| Reconstructing SARS-CoV-2 response signaling and regulatory networks J Ding, J Lugo-Martinez, Y Yuan, DN Kotton, Z Bar-Joseph BioRxiv, 2020.06. 01.127589, 2020 | 2 | 2020 |
Ziv Bar-JosephProfessor of Computational Biology and Machine Learning, School of Computer Science, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
