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Articles 1 - 6 of 6
Full-Text Articles in Bioinformatics
Computational And Experimental Investigation Into The Determinants Of Protein Structure, Folding, And Stability In The Β-Grasp Superfamily, John T. Bedford Ii
Computational And Experimental Investigation Into The Determinants Of Protein Structure, Folding, And Stability In The Β-Grasp Superfamily, John T. Bedford Ii
Chemistry & Biochemistry Theses & Dissertations
Elucidating the mechanisms of protein folding and unfolding is one of the greatest scientific challenges in basic science. The overarching goal is to predict three-dimensional structures from their amino acid sequences. Understanding the determinants of protein folding and stability can be facilitated through the study of evolutionarily related but diverse proteins. Insights can also be gained through the study of proteins from extremophiles that may more closely resemble the primordial proteins. In this doctoral research, three aims were accomplished to characterize the structure, folding and unfolding behavior within the β-grasp superfamily. We propose that the determinants of structure, stability, and …
A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose
A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose
Dissertations & Theses (Open Access)
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very poor patient prognosis (5-year survival of ≤ 7%). While transcriptional profiling has aided in the classification of this disease into at least two broader subtypes, this alone has so far been insufficient to inform on more nuanced patterns of oncogenic dependency. We hypothesized that a more comprehensive and granular characterization of PDAC disease diversity is required to establish relevant context for targeted therapy. To this end, we sought to establish an integrated platform to: i) more comprehensively characterize differential oncogenic signaling across our tumor models, and ii) establish …
Gene Co-Occurrence Networks Reflect Bacteriophage Ecology And Evolution, Jason W. Shapiro, Catherine Putonti
Gene Co-Occurrence Networks Reflect Bacteriophage Ecology And Evolution, Jason W. Shapiro, Catherine Putonti
Bioinformatics Faculty Publications
Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network …
Interactomics-Based Functional Analysis: Using Interaction Conservation To Probe Bacterial Protein Functions, J. Harry Caufield
Interactomics-Based Functional Analysis: Using Interaction Conservation To Probe Bacterial Protein Functions, J. Harry Caufield
Theses and Dissertations
The emergence of genomics as a discrete field of biology has changed humanity’s understanding of our relationship with bacteria. Sequencing the genome of each newly-discovered bacterial species can reveal novel gene sequences, though the genome may contain genes coding for hundreds or thousands of proteins of unknown function (PUFs). In some cases, these coding sequences appear to be conserved across nearly all bacteria. Exploring the functional roles of these cases ideally requires an integrative, cross-species approach involving not only gene sequences but knowledge of interactions among their products. Protein interactions, studied at genome scale, extend genomics into the field of …
Computational Methods For Biomarker Identification In Complex Disease, Amin Ahmadi Adl
Computational Methods For Biomarker Identification In Complex Disease, Amin Ahmadi Adl
USF Tampa Graduate Theses and Dissertations
In a modern systematic view of biology, cell functions arise from the interaction between molecular components. One of the challenging problems in systems biology with high-throughput measurements is discovering the important components involved in the development and progression of complex diseases, which may serve as biomarkers for accurate predictive modeling and as targets for therapeutic purposes. Due to the non-linearity and heterogeneity of these complex diseases, traditional biomarker identification approaches have had limited success at finding clinically useful biomarkers. In this dissertation we propose novel methods for biomarker identification that explicitly take into account the non-linearity and heterogeneity of complex …
A Multifaceted Approach Identifies Erbb2 And Erbb3 Proteins And Microrna-125b As Key Contributors To Prostate Cancer Progression, Danielle Weaver
A Multifaceted Approach Identifies Erbb2 And Erbb3 Proteins And Microrna-125b As Key Contributors To Prostate Cancer Progression, Danielle Weaver
Theses and Dissertations
Prostate cancer is the most common cancer affecting men today. Therefore, there is a strong need for accurate biomarkers and successful therapeutic treatments. A novel approach combining a computationally built protein-protein interaction network of proven microRNA protein targets with high throughput proteomics identified ErbB2 and ErbB3 as key proteins in prostate cancer. These results coupled with microRNA array screening of an androgen-independent prostate cancer progression model, substantiated by single microRNA analysis, suggested miR125b as a key tumor suppressor contributing to prostate cancer progression. miR125b expression was shown to be substantially increased in the non-tumorigenic P69 cell line compared to its …