SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boostingBin Yu, Qin Ma, Hongyan Zhou et al.|Bioinformatics|2019Cited by 186
GTB-PPI: Predict Protein–Protein Interactions Based on L1-Regularized Logistic Regression and Gradient Tree BoostingBin Yu, Qin Ma, Cheng Chen et al.|Genomics Proteomics & Bioinformatics|2020Cited by 56
SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boostingMinghui Wang, Hongyan Zhou, Bin Yu et al.|Neural Computing and Applications|2020Cited by 41
Predicting Golgi-Resident Protein Types Using Conditional Covariance Minimization With XGBoost Based on Multiple Features FusionHongyan Zhou, Bin Yu, Cheng Chen et al.|IEEE Access|2019Cited by 31
Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest AlgorithmMinghui Wang, Bin Yu, Lingling Yue et al.|Mathematics|2020Cited by 18