| iFeature: a python package and web server for features extraction and selection from protein and peptide sequences Z Chen, P Zhao, F Li, A Leier, TT Marquez-Lago, Y Wang, GI Webb, ... Bioinformatics 31 (14), 2499–2502, 2018 | 523 | 2018 |
| iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data Z Chen, P Zhao, F Li, TT Marquez-Lago, A Leier, J Revote, Y Zhu, ... Briefings in Bioinformatics, 2020 | 325 | 2020 |
| iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites J Song, Y Wang, F Li, T Akutsu, ND Rawlings, GI Webb, KC Chou Briefings in bioinformatics, 2019 | 218 | 2019 |
| GlycoMine: a machine learning-based approach for predicting N-, C-and O-linked glycosylation in the human proteome F Li, C Li, M Wang, GI Webb, Y Zhang, JC Whisstock, J Song Bioinformatics 31 (9), 1411-1419, 2015 | 186 | 2015 |
| Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome. F Li, C Li, TT Marquez-Lago, A Leier, T Akutsu, AW Purcell, AI Smith, ... Bioinformatics (Oxford, England), 2018 | 157 | 2018 |
| PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy J Song*, F Li*, A Leier, TT Marquez-Lago, T Akutsu, G Haffari, KC Chou, ... Bioinformatics 34 (4), 684-687, 2018 | 152 | 2018 |
| A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction S Mei, F Li, A Leier, TT Marquez-Lago, K Giam, NP Croft, T Akutsu, ... Briefings in Bioinformatics, 2020 | 143 | 2020 |
| PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework J Song, F Li, K Takemoto, G Haffari, T Akutsu, KC Chou, GI Webb Journal of theoretical biology 443, 125-137, 2018 | 134 | 2018 |
| iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization Z Chen, P Zhao, C Li, F Li, D Xiang, YZ Chen, T Akutsu, RJ Daly, GI Webb, ... Nucleic acids research 49 (10), e60-e60, 2021 | 130 | 2021 |
| An interpretable prediction model for identifying N7-methylguanosine sites based on XGBoost and SHAP Y Bi, D Xiang, Z Ge, F Li*, C Jia*, J Song* Molecular Therapy-Nucleic Acids, 2020 | 118 | 2020 |
| MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters M Zhang*, F Li*, TT Marquez-Lago, A Leier, C Fan, KC Chou, J Song, ... Bioinformatics, 2019 | 116 | 2019 |
| DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites F Li, J Chen, A Leier, T Marquez-Lago, Q Liu, Y Wang, J Revote, AI Smith, ... Bioinformatics, 2020 | 113 | 2020 |
| Large-scale comparative assessment of computational predictors for lysine post-translational modification sites Z Chen, X Liu, F Li, C Li, T Marquez-Lago, A Leier, T Akutsu, GI Webb, ... Briefings in bioinformatics, 2019 | 109 | 2019 |
| Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms L Wei, J Hu, F Li, J Song, R Su, Q Zou Briefings in Bioinformatics, 2020 | 106 | 2020 |
| Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences Z Chen, P Zhao, F Li, Y Wang, AI Smith, GI Webb, T Akutsu, A Baggag, ... Briefings in bioinformatics 21 (5), 1676–1696, 2020 | 105 | 2020 |
| DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites Q Liu, J Chen, Y Wang, S Li, C Jia*, J Song*, F Li* Briefings in Bioinformatics 22 (3), 2021 | 100 | 2021 |
| Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods F Li, Y Wang, C Li, TT Marquez-Lago, A Leier, ND Rawlings, G Haffari, ... Briefings in Bioinformatics, 2019 | 93 | 2019 |
| Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information F Li, A Leier, Q Liu, Y Wang, D Xiang, T Akutsu, GI Webb, AI Smith, ... Genomics, Proteomics & Bioinformatics, 2020 | 84 | 2020 |
| GlycoMinestruct: a new bioinformatics tool for highly accurate mapping of the human N-linked and O-linked glycoproteomes by incorporating structural features F Li, C Li, J Revote, Y Zhang, GI Webb, J Li, J Song, T Lithgow Scientific reports 6, 34595, 2016 | 79 | 2016 |
| Positive-unlabelled learning of glycosylation sites in the human proteome F Li, Y Zhang, AW Purcell, GI Webb, KC Chou, T Lithgow, C Li, J Song BMC Bioinformatics 20 (1), 112, 2019 | 75 | 2019 |
Jiangning (John) SongAssociate Professor, Biomedicine Discovery Institute and Data Futures Institute, Monash UniversityVerified email at monash.edu
