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Molecular Communication in Biological Cells: Foundational Study and Development of Computational Techniques

Zahmeeth Sayed Sakkaff, University of Nebraska - Lincoln

Abstract

Biological cells have the ability to sense and communicate information with each other and the environment through the exchange of molecules and chemical reactions. Understanding the way this information propagates in single or multiple cells is important since their behavior has an impact on human health, our environment, food, and its engineered control would enable the game-changing application. At the basis of these communications, the paradigm of Molecular Communication (MC) stands in the application of information and communication theory to model and analyze information exchange through chemical reactions and molecular transport. The Challenge stands in the application of MC to specific biochemical mechanisms at the basis of biological cells, where these mechanisms are only partially understood, and cell’s models do not always address the complexity of molecular processes. A solution stems from the analysis of what is currently known about the major processes to regulate their behavior. The objectives of this dissertation are to model and analyze cells’ natural communications with unconventional tools, from computer communication theory, and understand the potential of these tools in future applications. First, information propagation in cell signal transduction pathways is modeled to quantify how cells modify their behavior based on the environment. To demonstrate a potential application, this model is used to understand how impairments in this capability can be at the basis of cancer. Second, the impact of the information propagation on cells behavior is modeled and analyzed on cell metabolism for various input environmental conditions. An application of these research results is shown through the utilization of tools from coding theory to inform the efficient design of wet-lab experiments. For this, a computational tool named Run Flux Mutual Information Analysis (RFMIA) is developed to understand single or inter-species interactions. Last, the aforementioned concepts are extended to address the theoretical modeling of multi-scale integrated biological pathways, which encompass signal transduction, gene regulation, and metabolism, to provide an end-to-end perspective of MC through a biological cell. Overall, this research, which stems from results and technological developments in computer communications, explores novel realms, biology, where these concepts can be applied for innovative applications.

Subject Area

Communication|Bioinformatics|Computer science|Information science

Recommended Citation

Sakkaff, Zahmeeth Sayed, "Molecular Communication in Biological Cells: Foundational Study and Development of Computational Techniques" (2019). ETD collection for University of Nebraska-Lincoln. AAI22618454.
https://digitalcommons.unl.edu/dissertations/AAI22618454

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