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Biochimica Et Biophysica Acta. Gene Regulatory Mechanisms|June 11, 2022
Deep learning-based transcription factor activity for stratification of breast cancer patientsYuqiang Xiong, Shiyuan Wang, Haodong Wei, et al.Cell & Bioscience|February 28, 2023
A cost-effective machine learning-based method for preeclampsia risk assessment and driver genes discoveryHao Wang, Zhaoyue Zhang, Haicheng Li, et al.Journal of Cellular and Molecular Medicine|April 7, 2020
Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancerShiyuan Wang, Yakun Wang, Chunlu Yu, et al.Briefings in Bioinformatics|February 11, 2023
A computational framework of routine test data for the cost-effective chronic disease predictionMingzhu Liu, Jian Zhou, Qilemuge Xi, et al.Current Drug Targets|October 14, 2025
Clinical Deployment of Interpretable AI: Bridging Routine Clinical Tests and Proteomic Signatures for Preeclampsia Risk StratificationYuting Guo, Yuchao Liang, Ming Liu, et al.Briefings in Bioinformatics|December 1, 2023
Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapesMin Zou, Honghao Li, Dongqing Su, et al.Briefings in Functional Genomics|November 10, 2021
Prognostic and predictive value of a metabolic risk score model in breast cancer: an immunogenomic landscape analysisDongqing Su, Shiyuan Wang, Qilemuge Xi, et al.Briefings in Functional Genomics|March 29, 2022
Integrated multi-cohorts for characterizing the immunogenomic landscape and predicting drug response in triple-negative breast cancerDongqing Su, Meng Chi, Shiyuan Wang, et al.Methods (San Diego, Calif.)|July 17, 2024
Machine learning-based prediction of diabetic patients using blood routine dataHonghao Li, Dongqing Su, Xinpeng Zhang, et al.Molecular Therapy. Nucleic Acids|July 12, 2026
Decoding preeclampsia: A fusion of multi-view machine learning and multi-omics to identify putative inflammation-related mechanismsYuting Guo, Yuchao Liang, Lingxuan Liu, et al.Pageof 12