Introduction to computational modeling of biological systems; A guide to drying up your lab work

Abstract

Biological modeling is a quickly developing subsection of biology. Combining biology and mathematics to provide computational models that can predict and explain biological phenomena. Where classic models provide an overview of a system with connections to predict outcomes when changing a single component, computational models can simultaneously update every component in the system. Allowing for more sensitive and time-dependent effects to be observed. We demonstrate how a dynamic model can be created through the use of Ordinary Differential Equations (ODEs). These inform what the values for each compartment within the system is and how they change over time. To help explain we showcase a classical thermodynamic entropy model. The principles of ODEs are then expanded to a multi-compartment system. To describe distance-dependent systems such as bacterial spread on plates, development of roots, and self-organisation of tissues we introduce an imaginary space named a lattice. These multi-dimensional planes utilize coordinate systems to characterise individual positions in space and provide information about components within the proximity. Once the establishment of components in a biological model is explained, we delve into strategies to parameterize the system. Taken together this review gives an overview of the essential components to consider when creating biological models.