Скачать или смотреть Modeling for Dynamical Systems (Notes and Sample MATLAB code included)

Boolean modeling offers a mathematical approach to analyze complex dynamical systems with discrete states, representing components as binary variables ("on" or "off"). These models use Boolean functions to describe interactions between components and system dynamics over time, utilizing logical operations like AND, OR, and NOT. Boolean networks are then constructed using these to see how each variable changes in state over time. The dynamics of these networks involve understanding concepts like state space, attractors (stable states), cycles, periodicity, and transients (temporary states before stability). Applications of Boolean models span diverse fields including gene regulatory networks, synthetic biology, neuroscience, epidemiology, and control theory. Challenges in Boolean modeling include scalability, complexity, and real-world applicability, with future directions focusing on integrating these models with continuous and probabilistic approaches.


Notes: https://github.com/PodcastLearn/Bioph...

Sample MATLAB Code: https://github.com/PodcastLearn/Bioph...