Now showing items 1-5 of 5
Learning from Data in Radio Algorithm Design
(Virginia Tech, 2017-12-06)
Algorithm design methods for radio communications systems are poised to undergo a massive disruption over the next several years. Today, such algorithms are typically designed manually using compact analytic problem models. ...
Machine Learning Approaches for Identifying microRNA Targets and Conserved Protein Complexes
(Virginia Tech, 2017-04-27)
Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. This dissertation focuses on two interesting problems in bioinformatics research: ...
Spatiotemporal Informatics for Sustainable Forest Production Utilizing Forest Inventory and Remotely Sensed Data
(Virginia Tech, 2017-02-08)
The interrelationship between trees and humans is primordial. As pressures on natural resources grow and become more complex this innate connection drives an increased need for improved data and analytical techniques for ...
Computational Modeling of Planktonic and Biofilm Metabolism
(Virginia Tech, 2017-10-16)
Most of microorganisms are ubiquitously able to live in both planktonic and biofilm states, which can be applied to dissolve the energy and environmental issues (e.g., producing biofuels and purifying waste water), but can ...
DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks
(Virginia Tech, 2017-05-02)
With the abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other prior knowledge (PK), along with gene ...