MLPA: Detecting overlapping communities by multi-label propagation approach. - Qiguo Dai; Maozu Guo 001; Yang Liu 006; Xiaoyan Liu; Ling Chen (IEEE Congress on Evolutionary Computation, 2013)

Measuring gene functional similarity based on group-wise comparison of GO terms. - Zhixia Teng; Maozu Guo 001; Xiaoyan Liu; Qiguo Dai; Chunyu Wang 002; Ping Xuan (Bioinform., 2013)

CPL: Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network. - Qiguo Dai; Mao-Zu Guo 001; Xiao-Yan Liu; Zhixia Teng; Chunyu Wang 002 (J. Comput. Sci. Technol., 2014)

Recognizing spontaneous micro-expression from eye region. - Xiaodong Duan; Qiguo Dai; Xinhan Wang; Yuangang Wang; Zhichao Hua 004 (Neurocomputing, 2016)

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)

MHADTI: predicting drug-target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms. - Zhen Tian; Xiangyu Peng; Haichuan Fang; Wenjie Zhang; Qiguo Dai; Yangdong Ye (Briefings Bioinform., 2022)

MD-MLI: Prediction of miRNA-lncRNA Interaction by Using Multiple Features and Hierarchical Deep Learning. - Jinmiao Song; Shengwei Tian; Long Yu 001; Qimeng Yang; Yan Xing 004; Chao Zhang; Qiguo Dai; Xiaodong Duan (IEEE ACM Trans. Comput. Biol. 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)

DHNLDA: A Novel Deep Hierarchical Network Based Method for Predicting lncRNA-Disease Associations. - Fansen Xie; Ziqi Yang; Jinmiao Song; Qiguo Dai; Xiaodong Duan (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

ISLMI: Predicting lncRNA-miRNA Interactions Based on Information Injection and Second-Order Graph Convolution Network. - Jinmiao Song; Shengwei Tian; Long Yu 001; Qimeng Yang; Yuanxu Wang; Qiguo Dai; Xiaodong Duan (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Constructing discriminative feature space for LncRNA-protein interaction based on deep autoencoder and marginal fisher analysis. - Zhixia Teng; Yiran Zhang; Qiguo Dai; Chengyan Wu; Dan Li (Comput. Biol. Medicine, 2023)

stHGC: a self-supervised graph representation learning for spatial domain recognition with hybrid graph and spatial regularization. - Runqing Wang; Qiguo Dai; Xiaodong Duan; Quan Zou 001 (Briefings Bioinform., 2024)

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)

Hierarchical Negative Sampling Based Graph Contrastive Learning Approach for Drug-Disease Association Prediction. - Yuanxu Wang; Jinmiao Song; Qiguo Dai; Xiaodong Duan (IEEE J. Biomed. Health Informatics, 2024)

Dual-stream cross-modal fusion alignment network for survival analysis. - Jinmiao Song; Yatong Hao; Shuang Zhao; Peng Zhang; Qilin Feng; Qiguo Dai; Xiaodong Duan (Briefings Bioinform., 2025)

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)

Predicting circRNA-Drug Resistance Associations Based on a Multimodal Graph Representation Learning Framework. - Ziqiang Liu; Qiguo Dai; Xianhai Yu; Xiaodong Duan; Chunyu Wang 002 (IEEE J. Biomed. Health Informatics, 2025)