| UFold: fast and accurate RNA secondary structure prediction with deep learning L Fu#, Y Cao#, J Wu, Q Peng, Q Nie, X Xie Nucleic acids research 50 (3), e14-e14, 2022 | 104 | 2022 |
| A deep ensemble model to predict miRNA-disease association L Fu, Q Peng Scientific reports 7 (1), 14482, 2017 | 73 | 2017 |
| Predicting transcription factor binding in single cells through deep learning L Fu, L Zhang, E Dollinger, Q Peng, Q Nie, X Xie Science advances 6 (51), eaba9031, 2020 | 40 | 2020 |
| Integrated analysis of multimodal single-cell data with structural similarity Y Cao#, L Fu#, J Wu, Q Peng, Q Nie, J Zhang, X Xie Nucleic Acids Research 50 (21), e121-e121, 2022 | 35 | 2022 |
| Optimal aggregated charging analysis for PEVs based on driving pattern model D Wang, H Wang, J Wu, X Guan, P Li, L Fu 2013 IEEE Power & Energy Society General Meeting, 1-5, 2013 | 16 | 2013 |
| SAILER: scalable and accurate invariant representation learning for single-cell ATAC-seq processing and integration Y Cao#, L Fu#, J Wu, Q Peng, Q Nie, J Zhang, X Xie Bioinformatics 37 (Supplement_1), i317-i326, 2021 | 14 | 2021 |
| Predicting dna methylation states with hybrid information based deep-learning model L Fu, Q Peng, L Chai IEEE/ACM transactions on computational biology and bioinformatics 17 (5 …, 2019 | 12 | 2019 |
| LncDLSM: Identification of Long Non-coding RNAs with Deep Learning-based Sequence Model Y Wang, P Zhao, H Du, Y Cao, Q Peng, L Fu IEEE Journal of Biomedical and Health Informatics 27 (4), 2117-2127, 2023 | 5 | 2023 |
| A two-stage prediction method of news popularity only using content features Y Li, Q Peng, Z Sun, L Fu 2018 13th World Congress on Intelligent Control and Automation (WCICA), 767-772, 2018 | 5 | 2018 |
| KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations J Wu, Z Ning, Y Ding, Y Wang, Q Peng, L Fu Briefings in Bioinformatics, bbad292, 2023 | 3 | 2023 |
| Design and Application of a Non-wrapped Programmable Logic Controller (PLC) Laboratory Kit for Automatic Control Education Y Wang, X Ren, Z Jing, M Liu, Q Peng, L Fu 2022 20th International Conference on Information Technology Based Higher …, 2022 | 2 | 2022 |
| Unveiling inflammatory and prehypertrophic cell populations as key contributors to knee cartilage degeneration in osteoarthritis using multi-omics data integration Y Fan, X Bian, X Meng, L Li, L Fu, Y Zhang, L Wang, Y Zhang, D Gao, ... Annals of the Rheumatic Diseases, 2024 | 1 | 2024 |
| Bertnda: a model based on graph-bert and multi-scale information fusion for ncRNA-disease association prediction Z Ning, J Wu, Y Ding, Y Wang, Q Peng, L Fu IEEE Journal of Biomedical and Health Informatics, 2023 | 1 | 2023 |
| UFold: Fast and Accurate RNA Secondary Structure Prediction with Deep Learning Y Cao, L Fu, J Wu, Q Nie, X Xie bioRxiv, 2020 | 1 | 2020 |
| Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection E Liu, H Lyu, Y Liu, L Fu, X Cheng, X Yin Bioinformatics 40 (3), btae138, 2024 | | 2024 |
| KGRACDA: A Model Based on Knowledge Graph from Recursion and Attention Aggregation for CircRNA-disease Association Prediction Y Wang, M Ma, Y Xie, Q Peng, H Lyu, H Sun, L Fu bioRxiv, 2023.12. 04.569883, 2023 | | 2023 |
| CircRNA-disease inference using deep ensemble model based on triple association L Fu, H Du, Y Wang, Q Peng 2022 China Automation Congress (CAC), 2698-2704, 2022 | | 2022 |
| MKPLS: Multiple kernel partial least squares for transcription factor binding site identification L Chai, Q Peng, X Zhang, L Fu, S Sun 2017 Chinese Automation Congress (CAC), 2939-2944, 2017 | | 2017 |
