| Multimodal single cell data integration challenge: results and lessons learned C Lance, MD Luecken, DB Burkhardt, R Cannoodt, P Rautenstrauch, ... Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2022 …, 2022 | 71 | 2022 |
| ResPAN: a powerful batch correction model for scRNA-seq data through residual adversarial networks Y Wang, T Liu, H Zhao Bioinformatics 38 (16), 3942-3949, 2022 | 20 | 2022 |
| Evaluating the Utilities of Foundation Models in Single-cell Data Analysis T Liu, K Li, Y Wang, H Li, H Zhao bioRxiv, 2023.09. 08.555192, 2023 | 15 | 2023 |
| Muse-gnn: Learning unified gene representation from multimodal biological graph data T Liu, Y Wang, R Ying, H Zhao Advances in neural information processing systems 36, 24661-24677, 2023 | 14 | 2023 |
| Logicvista: Multimodal llm logical reasoning benchmark in visual contexts Y Xiao, E Sun, T Liu, W Wang arXiv preprint arXiv:2407.04973, 2024 | 9 | 2024 |
| Single-cell transcriptomic atlas of Alzheimer’s disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK … L Zhang, CH He, S Coffey, D Yin, IU Hsu, C Su, Y Ye, C Zhang, J Spurrier, ... medRxiv, 2023.02. 18.23286037, 2023 | 9 | 2023 |
| Evaluating the utilities of foundation models in single-cell data analysis T Liu, K Li, Y Wang, H Li, H Zhao bioRxiv, 2023.09. 08.555192, 2024 | 7 | 2024 |
| scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis H Zhao, T Liu, T Chen, W Zheng, X Luo | 6* | 2024 |
| Geneverse: A collection of Open-source Multimodal Large Language Models for Genomic and Proteomic Research T Liu, Y Xiao, X Luo, H Xu, WJ Zheng, H Zhao EMNLP 2024, 2024 | 2 | 2024 |
| CosGeneGate Selects Multi-functional and Credible Biomarkers for Single-cell Analysis T Liu, W Long, Z Cao, Y Wang, CH He, L Zhang, SM Strittmatter, H Zhao Briefings in Bioinformatics, 2024.05. 22.595428, 2024 | 2 | 2024 |
| Specular Reflection Detection and Removal Based on Deep Neural Network for Endoscope Images T Liu, J Chang, C Wang, L Yang EMBC 2021, 2021 | 2 | 2021 |
| Apply artificial neural network to solving manpower scheduling problem T Liu, L Zhang 2021 IEEE 4th international conference on big data and artificial …, 2021 | 2 | 2021 |
| CVQVAE: A representation learning based method for multi-omics single cell data integration T Liu, G Greenberg, I Shomorony Machine Learning in Computational Biology, 1-15, 2022 | 1 | 2022 |
| An Intelligent Model for Solving Manpower Scheduling Problems L Zhang, T Liu, Y Wang 2021 IEEE 4th International Conference on Big Data and Artificial …, 2021 | 1 | 2021 |
| Semi-supervised Knowledge Transfer Across Multi-omic Single-cell Data F Zhang, T Liu, Z Chen, X Peng, C Chen, XS Hua, X Luo, H Zhao Advances in Neural Information Processing Systems 37, 40861-40891, 2025 | | 2025 |
| UNICORN: Towards Universal Cellular Expression Prediction with an Explainable Multi-Task Learning Framework H Zhao, T Liu, T Huang, Y Lin, R Ying | | 2025 |
| UNICORN: Towards Universal Cellular Expression Prediction with an Explainable Multi-Task Learning Framework T Liu, T Huang, Y Lin, R Ying, H Zhao bioRxiv, 2025.01. 22.634371, 2025 | | 2025 |
| spEMO: Exploring the Capacity of Foundation Models for Analyzing Spatial Multi-Omic Data T Liu, T Huang, R Ying, H Zhao bioRxiv, 2025.01. 13.632818, 2025 | | 2025 |
| Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states T Liu, E De Brouwer, T Kuo, N Diamant, A Missarova, H Wang, M Hao, ... 29th Annual International Conference on Research in Computational Molecular …, 2025 | | 2025 |
| Modeling and predicting single-cell multi-gene perturbation responses with scLAMBDA G Wang, T Liu, J Zhao, Y Cheng, H Zhao bioRxiv, 2024.12. 04.626878, 2024 | | 2024 |
Hongyu ZhaoYale UniversityE-mail megerősítve itt: yale.edu
