Abstract
DNA is the genetic repository for all living organisms, and it is subject to constant changes caused by chemical and physical factors. Any change, if not repaired, erodes the genetic information and causes mutations and diseases. To ensure overall survival, robust DNA repair mechanisms and damage-bypass mechanisms have evolved to ensure that the DNA is constantly protected against potentially deleterious damage while maintaining its integrity. Not surprisingly, defects in DNA repair genes affect metabolic processes, and this can be seen in some types of cancer, where DNA repair pathways are disrupted and deregulated, resulting in genome instability. Mathematically modelling the complex network of genes and processes that make up the DNA repair network will not only provide insight into how cells recognise and react to mutations, but it may also reveal whether or not genes involved in the repair process can be controlled. Due to the complexity of this network and the need for a mathematical model and software platform to simulate different investigation scenarios, there must be an automatic way to convert this network into a mathematical model. In this paper, we present a topological analysis of one of the networks in DNA repair, specifically homologous recombination repair (HR). We propose a method for the automatic construction of a system of rate equations to describe network dynamics and present results of a numerical simulation of the model and model sensitivity analysis to the parameters. In the past, dynamic modelling and sensitivity analysis have been used to study the evolution of tumours in response to drugs in cancer medicine. However, automatic generation of a mathematical model and the study of its sensitivity to parameter have not been applied to research on the DNA repair network so far. Therefore, we present this application as an approach for medical research against cancer, since it could give insight into a possible approach with which central nodes of the networks and repair genes could be identified and controlled with the ultimate goal of aiding cancer therapy to fight the onset of cancer and its progression.