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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
81

MULTIOMICS EVALUATION OF THE EFFECT OF EZRIN INHIBITOR IN DIFFUSE LARGE B CELL LYMPHOMA REVEALS DYSREGULATION OF BCR SIGNALING, RHO GTPASE SIGNALING AND APOPTOSIS

Alayed, Khaled 23 May 2019 (has links)
No description available.
82

Integrated Analysis of Multi-Omics Data Using Sparse Canonical Correlation Analysis

Castleberry, Alissa 29 July 2019 (has links)
No description available.
83

Determination of the Structure of Human Testis Protein Maelstrom and Examination of Functional Differences among Human Genome Variants

Wobser, Madison June 30 April 2019 (has links)
No description available.
84

Noncoding RNA-Involved Interactions for Cancer Prognosis: A Prostate Cancer Study

Wang, Leying 08 October 2020 (has links)
No description available.
85

THE ROLE OF COMPLEX EVOLUTIONARY DYNAMICS IN MOLECULAR SEQUENCE ANALYSIS

Lucaci, Alexander January 2023 (has links)
Codon substitution models can be used to quantify selective pressure on molecular sequences. The work contained within this dissertation represents my efforts to create, validate, and test codon models, and to apply them to biologically diverse data sets. Specifically, my objective is to determine the impact and consequences of instantaneous multi-nucleotide mutational events (MH) on the statistical inference of evolutionary rate parameters. In evolutionary terms, MH events represent rare phenomena which may have strong effects on protein-coding genes. Evidence for MH events directly impact the patterns and processes of protein-coding gene evolution across species and time. My central hypothesis is that accounting for multi-nucleotide mutational events alters the estimation of evolutionary rate parameters and represents an alternative path a gene may embark upon during their evolutionary history. This hypothesis is fundamentally based on a synthesis of my own work, and others within the field, on the relationship of the evolutionary properties of functional coding regions of the genome. My rationale is that completion of my dissertation will result in the generation of new statistical methodologies and readily available computational implementations designed to identify key targets of evolutionary mechanisms, genomic patterns, and biological processes important for the functional adaptation of the genome as it relates to MH. My long-term goal is to develop novel strategies to improve the biological realism of statistical models of molecular sequence evolution. I accomplish this goal by addressing gaps in conventional protein-coding gene model assumptions and with the inclusion of additional biological, statistical, physiological, and evolutionary information. In this effort, I have created a codon model to account for MH events, with details described in Chapter 2. We have also made the model easily available on Datamonkey.org and provided several useful visualizations to aide in the interpretations of results. To better understand the evolution of protein-coding genes, I applied my methods and other existing methods in the field to explore potentially novel biological insights into a gene family, the heat shock proteins, which play an important role as a protein chaperone, and in another paper, Brain-Derived Neurotrophic Factor (BDNF), which plays an important role in brain development. I developed software pipelines, curated data, and provided visualizations for the interpretation of results. The publications associated with this work are highlighted in Chapters 3 and 4, respectively. To enable the exploration of molecular virology and the analysis of viral pathogens I developed “Rapid Assessment of Selection in CLades (RASCL)”: a novel application for the rapid assessment of molecular sequence evolution viral clades. I used RASCL to study the emergence and ongoing evolution of SARS-CoV-2 lineage and to identify key sites subject to adaptive evolution and the development of new viral lineages. Near-real-time pathogen molecular surveillance is an important part of understanding the spread of disease. Our development of scalable tools to analyze big datasets of viral pathogen sequences is a critical step forward for global public health. My methods and results can be used to translate existing molecular sequence data into novel insights, and to improve the understanding of important evolutionary systems, and all together constitute an accessible platform for quantifying selective pressure on molecular sequences. / Biology
86

Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions

Heekes, Alexa Storme 29 August 2022 (has links) (PDF)
HIV and Mycobacterium tuberculosis (Mtb) co-infection causes treatment and diagnostic difficulties, which places a major burden on health care systems in settings with high prevalence of both infectious diseases, such as South Africa. Human genetic variation adds further complexity, with variants affecting disease susceptibility and response to treatment. The identification of variants in African populations is affected by reference mapping bias, especially in complex regions like the Major Histocompatibility Complex (MHC), which plays an important role in the immune response to HIV and Mtb infection. We used a graph-based approach to identify novel variants in the MHC region within African samples without mapping to the canonical reference genome. We generated a host-pathogen functional interaction network made up of inter- and intraspecies protein interactions, gene expression during co-infection, drug-target interactions, and human genetic variation. Differential expression and network centrality properties were used to prioritise proteins that may be important in co-infection. Using the interaction network we identified 28 human proteins that interact with both pathogens (”bridge” proteins). Network analysis showed that while MHC proteins did not have significantly higher centrality measures than non-MHC proteins, bridge proteins had significantly shorter distance to MHC proteins. Proteins that were significantly differentially expressed during co-infection or contained variants clinically-associated with HIV or TB also had significantly stronger network properties. Finally, we identified common and consequential variants within prioritised proteins that may be clinically-associated with HIV and TB. The integrated network was extensively annotated and stored in a graph database that enables rapid and high throughput prioritisation of sets of genes or variants, facilitates detailed investigations and allows network-based visualisation.
87

A Gene Co-Expression Network Mining Approach for Differential Expression Analysis

Morgan, Daniel Colin 14 May 2015 (has links)
No description available.
88

Computational Approaches for Cancer Precision Medicine

Stetson, Lindsay C. 03 June 2015 (has links)
No description available.
89

FREQUENT SUBGRAPH MINING OF PERSONALIZED SIGNALING NETWORKS

Durmaz, Arda 30 August 2017 (has links)
No description available.
90

Novel bioinformatics tools for miRNA-Seq analysis, RNA structure visualization, and genome-wide repeat detection

Shi, Jieming 19 July 2017 (has links)
No description available.

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