Jan A. Vriezen
Bachelor of Arts
Statistical and Data Sciences
Cellular automata, Ecological modeling, Asocial interactions, Differential equation
The emergence of a so-called “superbug” which is a harmful bacterium that is resistant to existing antibiotics has led to an increasing demand for novel antibiotics. Previous studies have shown that an understanding of microbial diversity can explain bacterial coexistence and diversity which provides insight for drug discovery. To investigate the effect of interbacterial interactions on microbial diversity, a cellular automaton simulation model was first developed, then used. Different grid sizes, change of rule, spatial configuration, and different types of interaction matrices were considered and used to look at how the community structure expressed in relative presence (frequency) changes. The simulations have shown that regardless of different grid size, change of rule, and use of different types of interaction matrices, the community composition in the dynamic equilibrium obtained is constant.
2020 Aoi Ogawa. Access limited to the Smith College community and other researchers while on campus. Smith College community members also may access from off-campus using a Smith College log-in. Other off-campus researchers may request a copy through Interlibrary Loan for personal use
Ogawa, Aoi, "Estimating microbial diversity of toxin producing bacteria from soil using cellular automata" (2020). Honors Project, Smith College, Northampton, MA.
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