Dongqing Su
Harbin, 150081, China
Last Updated: 09/26/2026
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Found 19 publications
IRDRM: Exploring Biological Traits and Clinical Significance in Breast Cancer Through Gene Pairs and Somatic Mutation Profiles.
Journal: Interdisciplinary sciences, computational life sciences
Published: April 19, 2025
Deep Clustering-Based Metabolic Stratification of Non-Small Cell Lung Cancer Patients Through Integration of Somatic Mutation Profile and Network Propagation Algorithm.
Journal: Interdisciplinary sciences, computational life sciences
Published: September 30, 2024
Machine learning-based prediction of diabetic patients using blood routine data.
Journal: Methods (San Diego, Calif.)
Published: May 17, 2024
Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes.
Journal: Briefings in bioinformatics
Published: August 16, 2023
Structural deep clustering network for stratification of breast cancer patients through integration of somatic mutation profiles.
Journal: Computer methods and programs in biomedicine
Published: June 14, 2023
Integrated analysis of ovarian cancer patients from prospective transcription factor activity reveals subtypes of prognostic significance.
Journal: Heliyon
Published: February 17, 2023
Stratification of ovarian cancer patients from the prospect of drug target-related transcription factor protein activity: the prognostic and genomic landscape analyses.
Journal: Briefings in functional genomics
Published: October 31, 2022
A random forest-based metabolic risk model to assess the prognosis and metabolism-related drug targets in ovarian cancer.
Journal: Computers in biology and medicine
Published: October 04, 2022
Deep learning-based transcription factor activity for stratification of breast cancer patients.
Journal: Biochimica et biophysica acta. Gene regulatory mechanisms
Published: April 04, 2022
Integrated multi-cohorts for characterizing the immunogenomic landscape and predicting drug response in triple-negative breast cancer.
Journal: Briefings in functional genomics
Published: December 29, 2021
Characterized the diversity of ABCB1 subtypes in immunogenomic landscape for predicting the drug response in breast cancer.
Journal: Methods (San Diego, Calif.)
Published: December 10, 2021
Prognostic and predictive value of a metabolic risk score model in breast cancer: an immunogenomic landscape analysis.
Journal: Briefings in functional genomics
Published: August 26, 2021
Last Updated: 09/26/2026