Integrative Systems Biology and Multi-Omics Methodologies for Translational Research in Chronic Diseases

TOPICAL COLLECTIONS

Guest Editors

Ge Zhang

Department of Cardiology, Zhengzhou University

Ge Zhang, MD, PhD, is a physician-scientist in the Department of Cardiology at Zhengzhou University.His research focuses on basic translational research and proactive health studies for major cardiovascular diseases using machine-learning and multi-omics clinical big data to advance precision medicine in major cardiovascular diseases. He has been recognized as a Highly Downloaded Author and a High Contributor to Open Science (twice) by Wiley. Dr. Zhang has published extensively in high-impact journals such as Nature Communications, European Heart Journal, The Journal of Clinical Investigation, and Journal of Translational Medicine, with multiple first- or corresponding-author papers. He is also actively involved in translational research, holding several national invention patents and software copyrights related to cardiovascular risk assessment systems. Dr. Zhang currently serves as a guest editor, editorial board member, or reviewer for multiple international journals and is committed to promoting reproducible, methodologically rigorous biomedical research.

Kaisaierjiang Kadier

Department of Cardiology, The First Affiliated Hospital of Xinjiang Medical University

Dr. Kaisaierjiang Kadier is an assistant researcher and MD at the First Affiliated Hospital of Xinjiang Medical University, specializing in the clinical application of artificial intelligence in cardiovascular medicine. His research centers on developing intelligent diagnostic frameworks, ranging from non-invasive multi-channel heart sound analysis and deep learning-based ECG interpretation to the precision optimization of invasive imaging, specifically optical coherence tomography for coronary assessment.By integrating multimodal deep learning with large-scale epidemiological data from the public database, he investigates systemic risk factors and anti-aging markers related to cardiovascular health. To date, Dr. Kadier has authored over 30 peer-reviewed publications in international journals. In addition to his research, he contributes to the academic community as a frequent reviewer for multiple medical and scientific journals. His work aims to bridge the gap between advanced machine learning and individualized clinical precision medicine.

Shiqian Zhang

Nankai University

Shiqian Zhang, MD, focuses on the diagnosis and pathogenesis of colorectal cancer. His scientific research work deeply integrates clinical medicine and cutting-edge computing technology, and is committed to analyzing the molecular characteristics and evolutionary rules of colorectal cancer through bioinformatics and machine learning methods. Currently, the research focuses include developing early diagnostic models based on multi-omics data, mining key drivers of disease progression, and building interpretable prediction algorithms to aid clinical decision-making.By integrating high-throughput sequencing data and clinical information, Dr. Shiqian Zhang has made breakthroughs in the fields of tumor heterogeneity, microenvironmental interaction, and treatment resistance, promoting the practice and application of precision medicine in the field of colorectal cancer.

Ge-Zhang

Department of Gastroenterology, the First Affiliated Hospital of Zhengzhou University

Ge-Zhang, MD, is a physician-scientist at Zhengzhou University, where he focuses on the molecular mechanisms and therapeutic strategies of gastrointestinal cancers. His research primarily investigates tumor pathogenesis, treatment resistance, and microenvironmental regulation, with recent expansion into the emerging interdisciplinary field linking circadian rhythm disruption to cancer progression and therapeutic response.By integrating molecular biology, biomaterials, and translational research approaches, Dr. Zhang aims to identify key signaling pathways and actionable therapeutic targets relevant to cancer treatment. He has published multiple first-author (including co–first author) studies in international journals such as Biomaterials, Cell Death Discovery, Clinical and Translational Medicine, and MedComm–Oncology, with his work receiving over 90 citations to date. His research contributes to advancing mechanistic understanding and translational innovation in oncology.

Collection Overview

Chronic diseases, including cardiovascular disorders, cancer, metabolic diseases, and chronic inflammatory conditions, remain the leading contributors to global morbidity and mortality. Their progression is driven by complex, multiscale biological processes that cannot be adequately captured by classical single-modality or single-disease analytical frameworks. In recent years, advances in artificial intelligence, systems biology, and multi-omics technologies have enabled integrative, data-driven approaches to dissect disease mechanisms, progression trajectories, and therapeutic responses across diverse chronic disease contexts.

This collection aims to provide protocols illustrating how AI-based modeling, multi-omics integration, and computational systems approaches can be effectively applied to chronic disease research. The collection highlights practical methodologies spanning data preprocessing, cross-omics feature integration, model development, validation strategies, and biological and clinical interpretability, with particular emphasis on translational applicability. By prioritizing methodological rigor and reproducibility over conceptual innovation, this collection bridges the gap between complex data analytics and biomedical research and application. It offers a methodological resource for researchers working across cardiovascular disease, oncology, and other major chronic diseases.