Synergistic Applications of Mechanistic Models and AI in Understanding Biology and Medicine

The integration of Mechanistic Modeling (MM) and Artificial Intelligence (AI) is transforming how we study biological systems and medical phenomena. While traditional mechanistic models, such as stochastic, ordinary, delay, and partial differential equations have long provided deep mechanistic insights, AI and machine learning offer powerful new tools for discovery, parameter estimation, and data-driven refinement of these models.This Research Topic focuses on the interdisciplinary integration of MM and AI across biological and medical sciences. By critically evaluating emerging approaches that unify mechanistic frameworks with AI methodologies, we aim to push the boundaries of biomedical research. Key primary objectives include exploring how AI enhances parameter estimation, model selection, and uncertainty quantification in classical MM; advancing data-driven methodologies for discovering biological laws directly from data; and developing hybrid frameworks that increase both model interpretability and the predictive strength of modern AI. Submissions should demonstrate the integration of MM approaches and AI or machine learning methodologies. Methodological or theoretical studies without biological relevance will be considered out of scope. We welcome contributions including, but not limited to, the following themes:• AI-enhanced parameter inference, sensitivity analysis, and uncertainty quantification for mechanistic models• Data-driven model discovery and learning of governing equations from empirical data• Hybrid modeling methods unifying physics-based, statistical, and deep learning approaches• AI-informed prediction, real-time control, and decision-making in health and disease management• Deep learning solutions for extracting actionable features from complex omics, imaging, or clinical datasets• Applications in infectious disease, systems and synthetic biology, personalized medicine, pharmacokinetics, ecological and population modeling, and multi-omics integrationWe welcome original research articles, methods papers, reviews, perspectives, and opinions. Topic editors: Majid Bani-Yaghoub, Md Yusuf Sarwar Uddin, Sara D Sony, Qiao Zhuang Source: https://www.frontiersin.org/research-topics/76523/synergistic-applications-of-mechanistic-models-and-ai-in-understanding-biology-and-medicine