| Positive-unlabeled learning in bioinformatics and computational biology: a brief review F Li, S Dong, A Leier, M Han, X Guo, J Xu, X Wang, S Pan, C Jia, Y Zhang, ... Briefings in bioinformatics 23 (1), bbab461, 2022 | 61 | 2022 |
| Porpoise: a new approach for accurate prediction of RNA pseudouridine sites F Li*, X Guo*, P Jin, J Chen, D Xiang, J Song, LJM Coin Briefings in bioinformatics 22 (6), bbab245, 2021 | 54 | 2021 |
| iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities J Xu, F Li, C Li, X Guo, C Landersdorfer, HH Shen, AY Peleg, J Li, S Imoto, ... Briefings in Bioinformatics, 2023 | 46 | 2023 |
| Computational analysis and prediction of PE_PGRS proteins using machine learning F Li, X Guo, D Xiang, ME Pitt, A Bainomugisa, LJM Coin Computational and Structural Biotechnology Journal 20, 662-674, 2022 | 22 | 2022 |
| Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations Y Bi, F Li, X Guo, Z Wang, T Pan, Y Guo, GI Webb, J Yao, C Jia, J Song Briefings in Bioinformatics, bbac467, 2022 | 21 | 2022 |
| ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species R Chen, F Li, X Guo, Y Bi, C Li, S Pan, LJM Coin, J Song Briefings in Bioinformatics 24 (3), bbad170, 2023 | 17 | 2023 |
| Digerati – a multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins F Li*, X Guo*, Y Bi, R Jia, ME Pitt, S Pan, S Li, RB Gasser, LJM Coin, ... Computers in Biology and Medicine, 2023 | 10 | 2023 |
| ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction F Li, C Wang, X Guo, T Akutsu, GI Webb, LJM Coin, L Kurgan, J Song Briefings in Bioinformatics 24 (6), bbad372, 2023 | 9 | 2023 |
| Advancing mRNA subcellular localization prediction with graph neural network and RNA structure F Li, Y Bi, X Guo, X Tan, C Wang, S Pan Bioinformatics 40 (8), btae504, 2024 | 5 | 2024 |
| TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters Y Zhu, F Li, X Guo, X Wang, LJM Coin, GI Webb, J Song, C Jia Briefings in Bioinformatics 24 (4), bbad209, 2023 | 5 | 2023 |
| COPPER: an ensemble deep-learning approach for identifying exclusive virus-derived small interfering RNAs in plants Y Bu, C Jia, X Guo, F Li, J Song Briefings in Functional Genomics, 2022 | 5 | 2022 |
| scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks T Liu, C Jia, Y Bi, X Guo, Q Zou, F Li Briefings in Bioinformatics 25 (6), bbae486, 2024 | 2 | 2024 |
| MetalPrognosis: A Biological Language Model-Based Approach for Disease-Associated Mutations in Metal-Binding Site Prediction R Jia, Z He, C Wang, X Guo, F Li IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024 | 1 | 2024 |
| MERITS: a web-based integrated Mycobacterial PE/PPE protein database Z He, C Wang, X Guo, H Sun, Y Bi, ME Pitt, C Li, J Song, LJM Coin, F Li Bioinformatics Advances 4 (1), vbae035, 2024 | 1 | 2024 |
| Allocator is a graph neural network-based framework for mRNA subcellular localization prediction F Li, Y Bi, X Guo, X Tan, C Wang, S Pan | | 2023 |
| Predicting pseudouridine sites with Porpoise X Guo, F Li, J Song Computational Epigenomics and Epitranscriptomics, 2023 | | 2023 |
Fuyi LiSAiGENCI, The University of AdelaideПотвърден имейл адрес: adelaide.edu.au
