Biostatistics Commons^™

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

Development Of A Dna Methylation Multiplex Assay For Body Fluid Identification And Age Determination, Quentin Gauthier

FIU Electronic Theses and Dissertations

For forensic laboratories, the determination of body fluid origin of samples collected at a crime scene are typically presumptive and often destructive. However, given that in certain cases the presence of DNA is not in dispute and rather where the DNA came from is of primary concern, new methodologies are needed. Epigenetic modifications, such as DNA methylation, affect gene expression in every cell of every mammal. These DNA methylation patterns typically are observed as the addition of a methyl group on the 5’ carbon of a cytosine followed by guanine (CpG). Methylation patterns have been observed to change in response …

Computational Analysis Of Large-Scale Trends And Dynamics In Eukaryotic Protein Family Evolution, Joseph Boehm Ahrens

FIU Electronic Theses and Dissertations

The myriad protein-coding genes found in present-day eukaryotes arose from a combination of speciation and gene duplication events, spanning more than one billion years of evolution. Notably, as these proteins evolved, the individual residues at each site in their amino acid sequences were replaced at markedly different rates. The relationship between protein structure, protein function, and site-specific rates of amino acid replacement is a topic of ongoing research. Additionally, there is much interest in the different evolutionary constraints imposed on sequences related by speciation (orthologs) versus sequences related by gene duplication (paralogs). A principal aim of this dissertation is to …

Exposure To Estrogenic Endocrine Disrupting Chemicals And Brain Health, Mark Preciados

FIU Electronic Theses and Dissertations

The overall objective of this dissertation was to examine exposures to the estrogenic endocrine disrupting chemicals (EEDCs), phthalates, bisphenol-A (BPA), and the metalloestrogens cadmium (Cd), arsenic (As), and manganese (Mn) in an older geriatric aged-population and examine associations with brain health. Given the evidence that EEDCs affect brain health and play a role in the development of cognitive dysfunction and neurodegenerative disease, and the constant environmental exposure through foods and everyday products has led this to becoming a great public health concern. Using a bioinformatic approach to find nuclear respiratory factor 1 (NRF1) gene targets involved in mitochondrial dysfunction, that …

Simulation And Application Of Binary Logic Regression Models, Jobany J. Heredia Rico

FIU Electronic Theses and Dissertations

Logic regression (LR) is a methodology to identify logic combinations of binary predictors in the form of intersections (and), unions (or) and negations (not) that are linearly associated with an outcome variable. Logic regression uses the predictors as inputs and enables us to identify important logic combinations of independent variables using a computationally efficient tree-based stochastic search algorithm, unlike the classical regression models, which only consider pre-determined conventional interactions (the “and” rules). In the thesis, we focused on LR with a binary outcome in a logistic regression framework. Simulation studies were conducted to examine the performance of LR under the …

Network Construction And Graph Theoretical Analysis Of Functional Language Networks In Pediatric Epilepsy, Anas Salah Eddin

FIU Electronic Theses and Dissertations

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ …