Jiangning Song

Latest

• BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria
• DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy
• PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins
• Bastion3: a two-layer ensemble predictor of type III secreted effectors
• Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework
• Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches
• Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors
• Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI
• FusC, a member of the M16 protease family acquired by bacteria for iron piracy against plants
• PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection
• POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles
• SecretEPDB: a comprehensive web-based resource for secreted effector proteins of the bacterial types III, IV and VI secretion systems