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Articles 1 - 5 of 5
Full-Text Articles in Life Sciences
Leveraging Mass Spectrometry-Based Proteomics And Post-Translational Modifications For System-Wide Understanding Of Bioenergy Plants And Their Environment, Him K. Shrestha
Doctoral Dissertations
Bioenergy research focuses on utilizing renewable biomass feedstocks to produce biofuels and bioproducts to address growing concerns about energy security and climate change. To better understand the details of bioenergy crop production and conversion to bioproducts, it is essential to characterize bioenergy plants and their environments at a molecular systems level. Mass spectrometry has emerged as a promising technique for detailed proteomic information, including post-translational modifications (PTMs), of molecular processes and cellular functions of biological systems. In this dissertation, proteomic approaches have been optimized and implemented to deepen our understanding of the interaction of plants and their environment in a …
Systematic Evaluation Of Database Builds In Metaproteomics For The Advancement Of Microbiome Research, Katherine E. Ostrouchov
Systematic Evaluation Of Database Builds In Metaproteomics For The Advancement Of Microbiome Research, Katherine E. Ostrouchov
Masters Theses
The microscopic life that inhabits a human shares a unique bond with its host. Microbes perform many functions that are vital to the survival of the human species and have long been shown to regulate the absorption of nutrients and to promote immune function. A lack of exposure to certain microbes early in life, excessive antibiotic usage, and improper diet can perturb human microbiomes and lead to disease. Since the emergence of omic sequencing technologies, it has now become possible to measure and monitor the genes and proteins made by these microorganisms to better understand how they contribute to host …
Efficient Network Domination For Life Science Applications, Stephen K. Grady
Efficient Network Domination For Life Science Applications, Stephen K. Grady
Doctoral Dissertations
With the ever-increasing size of data available to researchers, traditional methods of analysis often cannot scale to match problems being studied. Often only a subset of variables may be utilized or studied further, motivating the need of techniques that can prioritize variable selection. This dissertation describes the development and application of graph theoretic techniques, particularly the notion of domination, for this purpose. In the first part of this dissertation, algorithms for vertex prioritization in the field of network controllability are studied. Here, the number of solutions to which a vertex belongs is used to classify said vertex and determine its …
Computational Analysis Of Transcriptional And Post-Transcriptional Feedback Loops In Development And Cell Differentiation, Benjamin Rigel Nordick
Computational Analysis Of Transcriptional And Post-Transcriptional Feedback Loops In Development And Cell Differentiation, Benjamin Rigel Nordick
Masters Theses
Regulation of gene expression is critical to organism development and health. Positive and negative feedback in networks of gene regulatory interactions are associated with the maintenance of distinct cell states/types or oscillations, respectively. Recent computational studies identified two structures of positive feedback relevant to establishment of cell type: interconnected transcriptional “high-feedback” loops and a purely post-transcriptional feedback loop arising from multiple microRNA molecules cooperatively regulating one mRNA. The goals of this work were to develop methods for analyzing often-unintuitive high-feedback loops in large networks, generalize the two new regulatory structures to consider oscillation, and further explore the ability of post-transcriptional …
Multi-Omic Systems Biological Analysis Of Host-Microbe Interactions, Piet Jones
Multi-Omic Systems Biological Analysis Of Host-Microbe Interactions, Piet Jones
Doctoral Dissertations
Systems biology offers the opportunity to understand the complex mechanisms of various biological phenomena. The wealth of data that is produced, at an increasing rate, provides the potential to meet this opportunity. Here we take an applied approach to integrate multiple omic level data sources in order to generate biologically relevant hypotheses. We apply a novel analysis pipeline to model both, in concert, the microbial and transcriptomic signature from COVID-19 positive patients. We show patients may suffer from an increased microbial burden, with an increased pathogen potential. Gene expression evidence further shows patients may exhibit a compromised barrier immunity, owing …