| Copy number variation is highly correlated with differential gene expression: a pan-cancer study X Shao, N Lv, J Liao, J Long, R Xue, N Ai, D Xu, X Fan BMC medical genetics 20, 1-14, 2019 | 267 | 2019 |
| CellTalkDB: a manually curated database of ligand–receptor interactions in humans and mice X Shao, J Liao, C Li, X Lu, J Cheng, X Fan Briefings in bioinformatics 22 (4), bbaa269, 2021 | 199 | 2021 |
| Uncovering an organ’s molecular architecture at single-cell resolution by spatially resolved transcriptomics J Liao, X Lu, X Shao, L Zhu, X Fan Trends in biotechnology 39 (1), 43-58, 2021 | 187 | 2021 |
| scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data X Shao, J Liao, X Lu, R Xue, N Ai, X Fan Iscience 23 (3), 2020 | 184 | 2020 |
| New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data X Shao, X Lu, J Liao, H Chen, X Fan Protein & cell 11 (12), 866-880, 2020 | 95 | 2020 |
| scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network X Shao, H Yang, X Zhuang, J Liao, P Yang, J Cheng, X Lu, H Chen, X Fan Nucleic acids research 49 (21), e122-e122, 2021 | 79 | 2021 |
| Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk X Shao, C Li, H Yang, X Lu, J Liao, J Qian, K Wang, J Cheng, P Yang, ... Nature Communications 13 (1), 4429, 2022 | 66 | 2022 |
| Knowledge graph-enhanced molecular contrastive learning with functional prompt Y Fang, Q Zhang, N Zhang, Z Chen, X Zhuang, X Shao, X Fan, H Chen Nature Machine Intelligence 5 (5), 542-553, 2023 | 61 | 2023 |
| De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution J Liao, J Qian, Y Fang, Z Chen, X Zhuang, N Zhang, X Shao, Y Hu, ... Nature Communications 13 (1), 6498, 2022 | 37 | 2022 |
| Multiplexing methods for simultaneous large‐scale transcriptomic profiling of samples at single‐cell resolution J Cheng, J Liao, X Shao, X Lu, X Fan Advanced Science 8 (17), 2101229, 2021 | 34 | 2021 |
| Network pharmacology study reveals energy metabolism and apoptosis pathways-mediated cardioprotective effects of Shenqi Fuzheng J Liao, C Hao, W Huang, X Shao, Y Song, L Liu, N Ai, X Fan Journal of ethnopharmacology 227, 155-165, 2018 | 32 | 2018 |
| Exploring the interaction between Salvia miltiorrhiza and human serum albumin: Insights from herb–drug interaction reports, computational analysis and experimental studies X Shao, N Ai, D Xu, X Fan Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 161, 1-7, 2016 | 31 | 2016 |
| Knowledge-aware contrastive molecular graph learning Y Fang, H Yang, X Zhuang, X Shao, X Fan, H Chen arXiv preprint arXiv:2103.13047, 2021 | 22 | 2021 |
| Prediction of adverse drug reactions by combining biomedical tripartite network and graph representation model R Xue, J Liao, X Shao, K Han, J Long, L Shao, N Ai, X Fan Chemical research in toxicology 33 (1), 202-210, 2019 | 20 | 2019 |
| Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace J Qian, J Liao, Z Liu, Y Chi, Y Fang, Y Zheng, X Shao, B Liu, Y Cui, W Guo, ... Nature Communications 14 (1), 2484, 2023 | 19 | 2023 |
| Revealing topics and their evolution in biomedical literature using Bio-DTM: a case study of ginseng Q Chen, N Ai, J Liao, X Shao, Y Liu, X Fan Chinese medicine 12, 1-9, 2017 | 13 | 2017 |
| scCATCH: Automatic annotation on cell types of clusters from single-cell RNA sequencing data. iScience, 23 (3), 100882 X Shao, J Liao, X Lu, R Xue, N Ai, X Fan March, 2020 | 9 | 2020 |
| Identify differential genes and cell subclusters from time-series scRNA-seq data using scTITANS L Shao, R Xue, X Lu, J Liao, X Shao, X Fan Computational and Structural Biotechnology Journal 19, 4132-4141, 2021 | 8 | 2021 |
| The future of molecular studies through the lens of large language models J Zhang, Y Fang, X Shao, H Chen, N Zhang, X Fan Journal of Chemical Information and Modeling 64 (3), 563-566, 2024 | 4 | 2024 |
| Reference-free cell-type annotation for single-cell transcriptomics using deep learning with a weighted graph neural network X Shao, H Yang, X Zhuang, J Liao, Y Yang, P Yang, J Cheng, X Lu, ... bioRxiv, 2020.05. 13.094953, 2020 | 4 | 2020 |
