Applications of multisource data-based dynamic modeling to cell-cell signaling and infectious disease spreading

Chen, D. (2024)

Doctoral Thesis

The emergence of complex diseases resulting from abnormal cell-cell signaling and the spread of infectious diseases caused by pathogens are significant threats to humanity. Unraveling the dynamic mechanisms underlying cell-cell signaling and infectious disease spreading is crucial for effective disease prevention and treatment. As science and technology advance, the availability and diversity of observational and experimental data related to these biological processes continue to grow. In this thesis, we integrate multisource data with dynamic modeling to investigate the biological mechanisms of Notch signaling in biological development and to develop prevention and control strategies for infectious diseases.

• Notch signaling
• Angiogenesis
• Vasculogenesis
• Cellular Potts model
• Respiratory infection
• COVID-19
• Threshold dynamics
• Optimization

• All authors: Chen, D.
• Supervisor: Merks, R.M.H.; Xiao, Y.
• Co-supervisor: Baker, D.A.
• Committee: Derks, G.L.A.; Doelman, A.; Jiang, Y.; Lin, W.; Boven, M. van; Loerakker, S.
• Qualification: Doctor (dr.)
• Awarding Institution: Mathematical Institute (MI), Faculty of Science, Leiden University
• Date: 2024-01-09