Life Sciences Commons^™

The Expanding Marine Built Environment And Biofilm Formation Processes, Rachel Mugge

Dissertations

The marine built environment (i.e., places or things made or modified by humans) in the northern Gulf of Mexico is rapidly expanding and includes over 2,000 known historic shipwrecks, nearly 4,100 artificial reefs, and other built structures for natural resource extraction, marine aquaculture, renewable energy generation, munitions dumping areas, and commercial and recreational activities. While these structures have the potential to develop into artificial reefs, acting as biodiversity hotspots that provide food and shelter and facilitate organism transport, it is unclear how they affect biodiversity and ecosystem function in the marine environment. The success of artificial reefs to become ecosystems …

Characterizing Endogenous Dicer Products To Unravel Novel Rnai Biogenesis Pathways, Jacob Oche Peter

Dissertations

ABSTRACT

RNA interference (RNAi) is a pervasive gene regulatory mechanism in eukaryotes based on the action of multiple classes of small RNA (sRNA). Exploiting RNAi pathways in non-model systems have great potential for creating potent RNAi technologies. Here, we accessed RNAi-mediated control of gene expression in the two-spotted spider mite, Tetranychus urticae (T. urticae) using engineered dsRNA designed to modulate the host RNAi pathway and increase RNAi efficacy. Analysis of Dicer (Dcr) generated fragments revealed how exogenous RNAs access the host RNAi pathway in this animal, opening avenues for designing RNAi technology for their control. Further, some organisms …

Knowledge-Based Analysis Of Genomic Expression Data By Using Different Machine Learning Algorithms For The Purpose Of Diagnostic, Prognostic Or Therapeutic Application, Venkata Jagan Mohan Thodima

Dissertations

With more and more biological information generated, the most pressing task of bioinformatics has become to analyze and interpret various types of data, including nucleotide and amino acid sequences, protein structures, gene expression profiling and so on. In this dissertation, we apply the data mining techniques of feature generation, feature selection, and feature integration with learning algorithms to tackle the problems of disease phenotype classification, clinical outcome and patient survival prediction from gene expression profiles.

We analyzed the effect of batch noise in microarray data on the performance of classification. Batchmatch, a batch adjusting algorithm based on double scaling method …