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Full-Text Articles in Other Applied Mathematics
Dna Self-Assembly Of Trapezohedral Graphs, Hytham Abdelkarim
Dna Self-Assembly Of Trapezohedral Graphs, Hytham Abdelkarim
Electronic Theses, Projects, and Dissertations
Self-assembly is the process of a collection of components combining to form an organized structure without external direction. DNA self-assembly uses multi-armed DNA molecules as the component building blocks. It is desirable to minimize the material used and to minimize genetic waste in the assembly process. We will be using graph theory as a tool to find optimal solutions to problems in DNA self-assembly. The goal of this research is to develop a method or algorithm that will produce optimal tile sets which will self-assemble into a target DNA complex. We will minimize the number of tile and bond-edge types …
Dna Complexes Of One Bond-Edge Type, Andrew Tyler Lavengood-Ryan
Dna Complexes Of One Bond-Edge Type, Andrew Tyler Lavengood-Ryan
Electronic Theses, Projects, and Dissertations
DNA self-assembly is an important tool used in the building of nanostructures and targeted virotherapies. We use tools from graph theory and number theory to encode the biological process of DNA self-assembly. The principal component of this process is to examine collections of branched junction molecules, called pots, and study the types of structures that such pots can realize. In this thesis, we restrict our attention to pots which contain identical cohesive-ends, or a single bond-edge type, and we demonstrate the types and sizes of structures that can be built based on a single characteristic of the pot that is …
Supersymmetry And The Math Of Adinkras, Ari Putt Spiesberger
Supersymmetry And The Math Of Adinkras, Ari Putt Spiesberger
Senior Projects Fall 2018
The purpose of this paper is to expand the dictionary of values related to parameterized supersymmetry values. These values, represented by Adinkras, are some of the most fascinating explanations of theoretical supersymmetry that exist. My goal was to approach and define an equivalence class on a specific value that had yet to be defined. I was able to do this, and in doing so, present information on a larger equivalence class in the field surrounding Adinkras.
Differentiating Between A Protein And Its Decoy Using Nested Graph Models And Weighted Graph Theoretical Invariants, Hannah E. Green
Differentiating Between A Protein And Its Decoy Using Nested Graph Models And Weighted Graph Theoretical Invariants, Hannah E. Green
Electronic Theses and Dissertations
To determine the function of a protein, we must know its 3-dimensional structure, which can be difficult to ascertain. Currently, predictive models are used to determine the structure of a protein from its sequence, but these models do not always predict the correct structure. To this end we use a nested graph model along with weighted invariants to minimize the errors and improve the accuracy of a predictive model to determine if we have the correct structure for a protein.
Neural Network Predictions Of A Simulation-Based Statistical And Graph Theoretic Study Of The Board Game Risk, Jacob Munson
Neural Network Predictions Of A Simulation-Based Statistical And Graph Theoretic Study Of The Board Game Risk, Jacob Munson
Murray State Theses and Dissertations
We translate the RISK board into a graph which undergoes updates as the game advances. The dissection of the game into a network model in discrete time is a novel approach to examining RISK. A review of the existing statistical findings of skirmishes in RISK is provided. The graphical changes are accompanied by an examination of the statistical properties of RISK. The game is modeled as a discrete time dynamic network graph, with the various features of the game modeled as properties of the network at a given time. As the network is computationally intensive to implement, results are produced …