11.A Strengths and Limitations of Different Types of Models
- Statistical model可以揭示概率关系，但不考虑其中的作用机制。
- Network models are essential for understanding the topology 拓扑结构of the system
- Network models are flexible and can be used for multiscale descriptions 多尺度描述of a system
11.B Potential and Limitations of Different Types of Models
- 拓扑学模型和动力学模型相互补充
The different modeling approaches have their strengths and weaknesses in terms of the knowledge they can provide.
Statistical models are very useful in providing in “big picture “ overview of relationships between distal entities e.g. genes and disease but do not tell anything about basis (i.e. mechanism) for the relationship.
Network models are essential to understand how the system is organized and its capability to process information and enable regulation. Network models do not help us predict how the system will change with respect to time.
Dynamical models enable us to understand and predict how the system changes with respect to time and space. However in large systems it does not help us understand the basis for distal input output relationships.
To have predictive understanding of systems we need all three modeling approaches
