ABSTRACT

This chapter examines why mathematical modelling provides a valuable framework for people to begin unravelling the seemingly interminable complexity of biological systems. Models essentially capture some physical system of interest, say a space shuttle, or a bacterial cell, or a human population where a communicable disease is spreading. Mathematical models capture these systems typically by means of mathematical equations. Modelling can help prioritise experiments that are most informative and shed light on system function. Modelling has led to several useful and actionable insights across biology, generating new and novel hypotheses and guiding wet-lab experiments. Many useful models exist to understand protein folding and protein–ligand interactions. The Lotka–Volterra Predator–Prey Model is a classic, deterministic, mechanistic, continuous-time, dynamic, single-scale model that captures the dynamics of two interacting species—a predator and a prey—in an environment. The ‘SIR model’ is a classic example of a simple yet useful mathematical model to capture the spread of infectious disease in a population.