A Stacked Ensemble Learning Framework with Heterogeneous Feature Combinations for Predicting ncRNA-Protein Interaction. - Qiguo Dai; Zhaowei Wang 005; Jinmiao Song; Xiaodong Duan; Maozu Guo 001; Zhen Tian (BIBM, 2020)

GraphCDA: a hybrid graph representation learning framework based on GCN and GAT for predicting disease-associated circRNAs. - Qiguo Dai; Ziqiang Liu; Zhaowei Wang 005; Xiaodong Duan; Maozu Guo 001 (Briefings Bioinform., 2022)

Predicting miRNA-disease associations using an ensemble learning framework with resampling method. - Qiguo Dai; Zhaowei Wang 005; Ziqiang Liu; Xiaodong Duan; Jinmiao Song; Maozu Guo 001 (Briefings Bioinform., 2022)

Predicting RBP Binding Sites of RNA With High-Order Encoding Features and CNN-BLSTM Hybrid Model. - Zhaowei Wang 005; Qiguo Dai; Jinmiao Song; Xiaodong Duan; Hongpeng Yang; Ziqi Yang (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

TGAAL: Combining Transformer-based GAN and active learning to identify the coding potential of sORFs in plant lncRNAs. - Yu Wang; Jun Meng; Shihao Xia; Haibin Li; Zhaowei Wang 005; Yushi Luan (BIBM, 2023)

A multi-granularity information-enhanced pre-training method for predicting the coding potential of sORFs in plant lncRNAs. - Shihao Xia; Jun Meng; Zhaowei Wang 005; Yu Wang; Haibin Li; Zhaojing Qin; Yushi Luan (BIBM, 2023)

PAMPred: A hierarchical evolutionary ensemble framework for identifying plant antimicrobial peptides. - Zhaowei Wang 005; Jun Meng; Haibin Li; Shihao Xia; Yu Wang; Yushi Luan (Comput. Biol. Medicine, 2023)

DeepPepPI: A deep cross-dependent framework with information sharing mechanism for predicting plant peptide-protein interactions. - Zhaowei Wang 005; Jun Meng; Qiguo Dai; Haibin Li; Shihao Xia; Ruirui Yang; Yushi Luan (Expert Syst. Appl., 2024)

miPEPPred-FRL: A Novel Method for Predicting Plant MiRNA-Encoded Peptides Using Adaptive Feature Representation Learning. - Haibin Li; Jun Meng; Zhaowei Wang 005; Youwei Tang; Shihao Xia; Yu Wang; Zhaojing Qin; Yushi Luan (J. Chem. Inf. Model., 2024)

Attention-augmented multi-domain cooperative graph representation learning for molecular interaction prediction. - Zhaowei Wang 005; Jun Meng; Haibin Li; Qiguo Dai; Xiaohui Lin 002; Yushi Luan (Neural Networks, 2025)