Why use systems modelling?

Mathematical modelling is used to analyse the dynamic interactions between several components of a biological system, with the aim to understand the behaviour of the system as a whole (1). With high-throughput omics data and network analysis, hypothesis design and the use of predictive models is becoming a necessary component to understand the mechanisms underlying complex biological systems, diseases, and drug action. 

Mathematical models help us answer the questions:

• How are complex regulatory processes connected?
• How does disruption of these processes contribute to the development of pathological conditions?

Mathematical models help us in decision making, for example to:

• Analyse systems perturbations
• Perform sensitivity analysis
• Assess the suitability of specific molecules as novel therapeutic targets
• Develop hypotheses to guide and design new experiments

A powerful example of mathematical modelling being successfully used in cancer research (2) is shown in Figure 1. This is a SBGN (Systems Biology Graphical Notation (3)) process diagram of a model that describes the IL13-induced signalling of JAK/STAT pathway in Hodgkin (L1236) and primary mediastinal B-cell lymphoma (MedB-1) cell lines, along with key reactions of the model. The model helps us to quantitatively predict possible perturbations, which allows us to identify potential therapeutic targets.