Doctoral Dissertations
Date of Award
5-2020
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Energy Science and Engineering
Major Professor
Michael A. Langston
Committee Members
Russell Zaretzki, Nina Fefferman, Audris Mockus
Abstract
High dimensional and complex biological data continues to burgeon, making the development and automation of data-driven algorithms and workflows ever-more important. Focusing on graph the-oretical methods, we study graph construction and analytics for two foundational problems. In the first, we explore techniques for the thresholding of simple, undirected, edge-weighted biologicalgraphs. In the second, we build resting state brain graphs from magnetoencephalographic data, on which we use a number of graph metrics to compare individuals, brainwaves and epoch lengths.In a separate effort, we move down the evolutionary ladder and take a look at the functional and metabolic differences between Escherichia coli phylotypes. Throughout, we develop novel data-driven methodologies and focus on exposing underlying assumptions of previous data-analysis workflows.
Recommended Citation
Bleker, Carissa Robyn, "Data-Driven Analytics for High-Throughput Biological Applications. " PhD diss., University of Tennessee, 2020.
https://trace.tennessee.edu/utk_graddiss/5894
Comments
My discipline is "Data Science and Engineering", but it is not listed.