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. 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 to investigate:

    1. How complex regulatory processes are connected?

    2. How disruption of these processes contribute to the development of pathological conditions?

  • Mathematical models help us in decision making

    • Analyse systems perturbations.

    • Perform sensitivity analysis.

    • Assess the suitability of specific molecules as novel therapeutic targets.

    • Develop hypotheses to guide and design new experiments

In Figure 1  you can see an example of a SBGN (Systems Biology Graphical Notation) process diagram of a model that describe the IL13-induced signalling of JAK/STAT pathway in Hodgkin (L1236) and primary mediastinal B-cell lymphoma (MedB-1) cell lines. The model helps us to quantitatively predict possible perturbations, which would allow us to identify potential therapeutic targets.

SBGN process diagram

Figure 1  The SBGN process diagram of lymphoma-derived cell lines MedB-1 and L1236 dynamic signalling network model, consisting of reactions (arrows) with enzymatic, mass action, or custom kinetics. Round-headed arrows indicate reaction catalysis, whereas bar-ended arrows show reaction inhibition. IL13 is used as input function of the system. Reactions and species coloured in grey are omitted in the L1236 model.

View the original model in BioModels Database.