Abstract
Systems biology is an important research field for understanding complex biological systems. By integrating various omics data and computational models, it reveals the interactions and dynamic behaviors of different biomolecules within the organism. Dynamic modeling, as a core tool in systems biology, helps researchers construct multi-scale biological system models through analysis of metabolic pathways, signal transduction pathways, etc., extending from the cellular level to whole cell simulations. This study is based on the latest research progress and explores the application of dynamic modeling in gene regulatory networks, drug discovery, personalized medicine, and synthetic biology, with a particular focus on the challenges and prospects of whole cell simulation. Dynamic modeling helps to enhance the understanding of biological systems and provides new solutions for fields such as personalized therapy and drug development. Future research will focus on how to address the challenges of data integration, model complexity, and computational power to drive further development in systems biology.
Cite
CITATION STYLE
Zhou, J., & Yan, S. (2024). Dynamic Modeling in Systems Biology: From Pathway Analysis to Whole-Cell Simulations. Computational Molecular Biology. https://doi.org/10.5376/cmb.2024.14.0016
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