Systematic tracking of coordinated differential network motifs identifies novel disease-related genes by integrating multiple data. - Kai Shi 004; Lin Gao 006; Bingbo Wang (Neurocomputing, 2016)

Inferring Dysregulated Pathways of Driving Cancer Subtypes Through Multi-omics Integration. - Kai Shi 004; Lin Gao 006; Bingbo Wang (ISBRA, 2018)

Multi-Similarities Integration and Network Projection to Identify Human Microbe-Disease Association. - Kai Shi 004; Lin Li; Bin Wang (EBIMCS, 2020)

Identifying Molecular Biomarkers for Diseases With Machine Learning Based on Integrative Omics. - Kai Shi 004; Wei Lin 003; Xing-Ming Zhao (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Predicting Microbe-Disease Associations via Multiple Layer Graph Convolutional Network and Attention Mechanism. - Kai Shi 004; Lin Li; Juehua Yu; Yi Zhang 044; Xiaolan Xie (ICBBS, 2022)

Deep Learning-based Mortality Prediction of COVID-19 Patients with Cardiovascular Disease. - Huilin Zheng; Yingyi Liang; Daming Zhang; Kai Shi 004; Luxi Dong; Xiaolan Xie (DSC, 2024)

MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework. - Kai Shi 004; Qiaohui Liu; Qingrong Ji; Qisheng He; Xing-Ming Zhao (Briefings Bioinform., 2024)