On optimal control policy for probabilistic Boolean network: a state reduction approach. - Xi Chen; Hao Jiang 009; Yushan Qiu; Wai-Ki Ching (BMC Syst. Biol., 2012)

Discovery of metabolite biomarkers: flux analysis and reaction-reaction network approach. - Limin Li; Hao Jiang 009; Yushan Qiu; Wai-Ki Ching; Vassilios S. Vassiliadis (BMC Syst. Biol., 2013)

Construction of Probabilistic Boolean Network for Credit Default Data. - Ruochen Liang; Yushan Qiu; Wai-Ki Ching (CSO, 2014)

On control of singleton attractors in multiple Boolean networks: integer programming-based method. - Yushan Qiu; Takeyuki Tamura; Wai-Ki Ching; Tatsuya Akutsu (BMC Syst. Biol., 2014)

On observability of attractors in Boolean Networks. - Yushan Qiu; Xiaoqing Cheng; Wai-Ki Ching; Hao Jiang 009; Tatsuya Akutsu (BIBM, 2015)

On Eigen-matrix translation method for classification of biological data. - Hao Jiang 009; Yushan Qiu; Xiaoqing Cheng; Wai-Ki Ching (J. Syst. Sci. Complex., 2015)

Mathematical models for biological networks and machine learning with applications. - Yushan Qiu (2015)

Unconstrained optimization in projection method for indefinite SVMs. - Hao Jiang 009; Wai-Ki Ching; Yushan Qiu; Xiaoqing Cheng (BIBM, 2016)

A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks. - Wenpin Hou; Yushan Qiu; Nobuyuki Hashimoto; Wai-Ki Ching; Kiyoko F. Aoki-Kinoshita (BMC Bioinform., 2016)

Exact Identification of the Structure of a Probabilistic Boolean Network from Samples. - Xiaoqing Cheng; Tomoya Mori; Yushan Qiu; Wai-Ki Ching; Tatsuya Akutsu (IEEE ACM Trans. Comput. Biol. Bioinform., 2016)

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence. - Hao Jiang 009; Wai-Ki Ching; Yushan Qiu; Xiaoqing Cheng (BMC Syst. Biol., 2017)

Novel Method for Singleton and Cyclic Attractor Observability in Boolean Networks. - Yushan Qiu; Yulong Huang; Shaobo Tan; Dongqi Li; Ada Chaeli van der Zijp-Tan; Ada Fong; Glen M. Borchert; Jingshan Huang (BIBM, 2018)

Stationary Mahalanobis kernel SVM for credit risk evaluation. - Hao Jiang 009; Wai-Ki Ching; Ka Fai Cedric Yiu; Yushan Qiu (Appl. Soft Comput., 2018)

Discovery of Boolean metabolic networks: integer linear programming based approach. - Yushan Qiu; Hao Jiang 009; Wai-Ki Ching; Xiaoqing Cheng (BMC Syst. Biol., 2018)

Exploring Observability of Attractor Cycles in Boolean Networks for Biomarker Detection. - Yushan Qiu; Yulong Huang; Shaobo Tan; Dongqi Li; Ada Chaeli van der Zijp-Tan; Glen M. Borchert; Hao Jiang 009; Jingshan Huang (IEEE Access, 2019)

On predicting epithelial mesenchymal transition by integrating RNA-binding proteins and correlation data via L1/2-regularization method. - Yushan Qiu; Hao Jiang 009; Wai-Ki Ching; Michael K. Ng 001 (Artif. Intell. Medicine, 2019)

Drug Side-Effect Profiles Prediction: From Empirical to Structural Risk Minimization. - Hao Jiang 009; Yushan Qiu; Wenpin Hou; Xiaoqing Cheng; Man Yi Yim; Wai-Ki Ching (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

HOMC: A Hierarchical Clustering Algorithm Based on Optimal Low Rank Matrix Completion for Single Cell Analysis. - Xiaoqing Cheng; Chang Yan; Hao Jiang 009; Yushan Qiu (ICIC (3), 2021)

Matrix factorization-based data fusion for the prediction of RNA-binding proteins and alternative splicing event associations during epithelial-mesenchymal transition. - Yushan Qiu; Wai-Ki Ching; Quan Zou 001 (Briefings Bioinform., 2021)

Prediction of RNA-binding protein and alternative splicing event associations during epithelial-mesenchymal transition based on inductive matrix completion. - Yushan Qiu; Wai-Ki Ching; Quan Zou 001 (Briefings Bioinform., 2021)

Unsupervised Learning Framework With Multidimensional Scaling in Predicting Epithelial-Mesenchymal Transitions. - Yushan Qiu; Hao Jiang 009; Wai-Ki Ching (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

MDICC: novel method for multi-omics data integration and cancer subtype identification. - Ying Yang; Sha Tian; Yushan Qiu; Pu Zhao; Quan Zou 001 (Briefings Bioinform., 2022)

A high-order norm-product regularized multiple kernel learning framework for kernel optimization. - Hao Jiang 009; Dong Shen; Wai-Ki Ching; Yushan Qiu (Inf. Sci., 2022)

scHOIS: Determining Cell Heterogeneity Through Hierarchical Clustering Based on Optimal Imputation Strategy. - Xiaoqing Cheng; Chang Yan; Hao Jiang 009; Yushan Qiu (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

PCB: A pseudotemporal causality-based Bayesian approach to identify EMT-associated regulatory relationships of AS events and RBPs during breast cancer progression. - Liangjie Sun; Yushan Qiu; Wai-Ki Ching; Pu Zhao; Quan Zou 001 (PLoS Comput. Biol., 2023)

SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data. - Yushan Qiu; Chang Yan; Pu Zhao; Quan Zou 001 (Briefings Bioinform., 2023)

ConSpaS: a contrastive learning framework for identifying spatial domains by integrating local and global similarities. - Siyao Wu; Yushan Qiu; Xiaoqing Cheng (Briefings Bioinform., 2023)

GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering. - Lu-Bin Cui; Guiliang Guo; Michael K. Ng 001; Quan Zou 001; Yushan Qiu (Briefings Bioinform., 2024)

scMNMF: a novel method for single-cell multi-omics clustering based on matrix factorization. - Yushan Qiu; Dong Guo; Pu Zhao; Quan Zou 001 (Briefings Bioinform., 2024)

AGML: Adaptive Graph-Based Multi-Label Learning for Prediction of RBP and as Event Associations During EMT. - Yushan Qiu; Wensheng Chen; Wai-Ki Ching; Hongmin Cai; Hao Jiang 009; Quan Zou 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

Ensemble machine learning-based pre-trained annotation approach for scRNA-seq data using gradient boosting with genetic optimizer. - Osama Elnahas; Waleed M. Ead; Yushan Qiu; Jian Lu (BMC Bioinform., 2025)