Life Sciences Commons^™

Exploring Soil Microbial Dynamics In Southern Appalachian Forests: A Systems Biology Approach To Prescribed Fire Impacts, Saad Abd Ar Rafie

Doctoral Dissertations

Prescribed fires in Southern Appalachian forests are vital in ecosystem management and wildfire risk mitigation. However, understanding the intricate dynamics between these fires, soil microbial communities, and overall ecosystem health remains challenging. This dissertation addresses this knowledge gap by exploring selected aspects of this complex relationship across three interconnected chapters.

The first chapter investigates the immediate effects of prescribed fires on soil microbial communities. It reveals subtle shifts in porewater chemistry and significant increases in microbial species richness. These findings offer valuable insights into the interplay between soil properties and microbial responses during the early stages following a prescribed fire. …

Regulation Of Protein Synthesis In Arabidopsis Thaliana Through A Bioinformatic And Mathematical Lens, Ricardo Andres Urquidi Camacho

Doctoral Dissertations

Organisms exist under constantly varying environmental and internal conditions, which necessitate the differential regulation of gene expression. To synthesize proteins, the ribosome translates the information encoded in the nucleotide sequence of an mRNA into the final, functional amino acid sequence. Knockouts of ribosomal proteins lead to lethality. One such protein is the ribosomal protein 6 of the small subunit (eS6/RPS6). We confirmed that the knockout of either one of two eS6 paralogs in Arabidopsis leads to stunted growth and chlorosis. Here, these phenotypes have been further characterized in seedlings by precisely quantifying the ribosome loading of mRNAs as well as …

Application Of Machine Learning Approaches To Empower Drug Development, Yue Shen

Doctoral Dissertations

Human health, one of the major topics in Life Science, is facing intensified challenges, including cancer, pandemic outbreaks, and antimicrobial resistance. Thus, new medicines with unique advantages, including peptide-based vaccines and permeable small molecule antimicrobials, are in urgent need. However, the drug development process is long, complex, and risky with no guarantee of success. Also, the improvements in techniques applied in genomics, proteomics, computational biology, and clinical trials significantly increase the data complexity and volume, which imposes higher requirements on the drug development pipeline. In recent years, machine learning (ML) methods were employed to support drug development in various aspects …