mais.py (Mouse Artificial Immune System): A Python library for the hybridization of genetic algorithms with an artificial immune system

Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modelling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology models of this kind assume, e.g. that both the number of viruses and the number of mouse cells susceptible of being infected change according to their interaction, as stated in the ODE model. However, viruses can undergo mutations and consequently evolve inside the mouse, whereas the mouse in turn displays evolutionary mechanisms through its immune system, e.g. clonal selection, defending against the invading virus. We propose an evolutionary WHD model simulating the coexistence of an evolving invader within a host. In addition, instead of using ODEs we developed an alternative methodology consisting in the hybridization of a genetic algorithm with an artificial immune system. For this purpose we have designed mais.py (Mouse Artificial Immune System), a Python library for the hybridization of genetic algorithms with artificial immune system algorithms. Aside from the model interest in biology and its potential clinical use, the proposed WHD model may be useful in those cases where the invader exhibits evolutionary changes: in the design of anti-virus software, malware intrusion detection algorithms in corporation's computer systems, etc. The software successfully simulates two intruder detection paradigms (nonself-self, nonself-danger) in which nonself represents an evolving invader or guess (e.g. virus, computer program, etc.) and the self the infected host (e.g. mouse, computer memory, etc.). Simulation results open up the possibility of simulating environments in which two entities (guest vs. host) compete evolutionarily with each other when occupying the same space (e.g. organ cells, computer memory, network, etc.).