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Bioinformatics (Oxford, England)|October 1, 2019
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sitesFuyi Li, Jinxiang Chen, André Leier, et al.
Bioinformatics (Oxford, England)|August 9, 2019
PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteinsYanju Zhang, Sha Yu, Ruopeng Xie, et al.
Bioinformatics (Oxford, England)|June 28, 2018
Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteomeFuyi Li, Chen Li, Tatiana T Marquez-Lago, et al.
Briefings in Bioinformatics|January 17, 2021
Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I moleculesShutao Mei, Fuyi Li, Dongxu Xiang, et al.
Bioinformatics (Oxford, England)|March 17, 2018
Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectorsJiawei Wang, Bingjiao Yang, André Leier, et al.
Briefings in Bioinformatics|June 18, 2019
A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding predictionShutao Mei, Fuyi Li, André Leier, et al.
Nucleic Acids Research|May 7, 2022
iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data setsZhen Chen, Xuhan Liu, Pei Zhao, et al.
Briefings in Bioinformatics|October 5, 2018
Large-scale comparative assessment of computational predictors for lysine post-translational modification sitesZhen Chen, Xuhan Liu, Fuyi Li, et al.
Bioinformatics (Oxford, England)|November 3, 2018
Bastion3: a two-layer ensemble predictor of type III secreted effectorsJiawei Wang, Jiahui Li, Bingjiao Yang, et al.
Briefings in Bioinformatics|November 30, 2017
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approachesJiawei Wang, Bingjiao Yang, Yi An, et al.
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