Electrical and Electronic Engineering - Theses
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ItemModelling of C. elegans & cover time of T cells in the liver( 2017)Mathematical modelling is an essential approach for biologists, enabling them to investigate complex biological systems. Today, computational models are widely used to simulate biological processes, suggest hypothesis, and set up new experiments. This work is an attempt to discover the value of mathematical tools for understanding complex biological systems, such as electrical activity in neurons, and how they enable behaviours like locomotion, and such as the function of the immune system, and how immune cells patrol throughout the body. This thesis consists of two main parts. The overall objective of the first part is to use mathematical descriptions and computer simulations for understanding how biological neural networks work to generate different complex behaviours. The first part deals with different aspects of modelling of C. elegans. After a quick introduction to the biology and especially the neuronal network of the worm, several computational models of the nervous system and behaviours of C. elegans from the literature will be discussed. We will simulate the transmission of signals in the neural circuit of C. elegans from sensory neurons to motor neurons. Then, motivated by the hypothesis that the same neuronal structure can be used to generate different locomotive reactions to various sensory signals, we will show how a generic model of the neuronal network of the worm is able to produce two different behaviours based on two distinct sensory inputs from the environment. Finally, we will use Algorithmic Information Theory to analyse the complexity of the worms’ behaviours when they are subjected to changes in the temperature or food concentration in their environment. The broad objective of part two again is to apply mathematical tools to describe the function of complex biological systems like immune cells. The focus of the second part is on the movement of T cells. We will analyse data sets of recorded movement of T cells on the epidermis, dermis and lymph nodes to investigate their movement pattern. Then, in order to produce a coarse estimate of the cover time of T cells in the mouse liver, we will construct a discretised model of the mouse liver with nodes visited by random walkers representing T cells. Using this first-generation mathematical model, we will show how to compute the time needed to cover a given percentage of the liver in the given time by certain number of immune cells.