This thesis shows how to use Operations Research tools, e.g. Markov chains, optimization, game theory, and matchings, to understand problems that appear in biological contexts. We focus on two biological systems – the activation of the immune system in response to pathogens, and the metabolism of communities of different species of microbes.
In Chapter 1, we study a Markov chain model of the activation of individual T-cells, and use the model to analyze how cells make trade-offs between various metrics such as speed and accuracy. In Chapter 2, we provide a detailed model of microbial community metabolism and show how incorporating aspects of game theory and dynamic stability can improve predictions of the behavior of microbial communities. Chapter 3 takes a matching approach to modeling microbial community metabolism by modeling the relationship between species and their environment using the stable marriage problem.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/zvrk-sk21 |
| Date | January 2023 |
| Creators | Perry, Mitchell |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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