Computational Biology Commons^™

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Complex Biosystems PhD Program: Dissertations

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …

Predicting Marine Teleost Responses To Ocean Warming And Pollution, Akila Harishchandra

Electronic Theses and Dissertations

Ocean warming and pollution are two detrimental anthropogenic factors causing rapid marine ecosystem degradation recorded in the past decades. These factors alter the marine environment intolerable for many marine species, forcing them to either adapt or shift their contemporary habitat ranges to reduce the extinction risk embedded with environmental degradation. Estimating marine species’ habitat range shifts, and their potential for developing adaptive mechanisms are critical for ecosystem conservation and management, human health risk assessment, and climate change vulnerability assessments. Given that, for the first chapter of this thesis, we focused on developing a species distribution model (SDM) integrating marine species …

Exploration Of The Immune Landscape Of Ebv-Associated Gastric Cancers, Mikhail Salnikov

Electronic Thesis and Dissertation Repository

Epstein–Barr virus (EBV) is a gammaherpesvirus associated with 9% of all gastric cancers (GCs). EBV-associated GCs (EBVaGCs) are pathologically and clinically distinct entities from EBV-negative GCs (EBVnGCs), with EBVaGCs exhibiting differential molecular pathology and patient prognosis. The purpose of this thesis is to investigate the tumor microenvironment (TME) of EBVaGCs, which has not been explored in-depth. We hypothesize that EBVaGCs and EBVnGCs are also distinct in terms of the molecular immune landscape. We employed over 400 stomach adenocarcinoma (STAD) samples from The Cancer Genome Atlas (TCGA), as well as a single cell dataset, for the construction of a web suite …

Mining Sars-Cov-2 Phylogenetic Trees To Estimate Circulating Infections And Patterns Of Migration, Erin V. Brintnell

Electronic Thesis and Dissertation Repository

The SARS-CoV-2 pandemic led to the formation of very large databases of genomic viral data. These databases contain information on transmission dynamics, emergence and evolution of SARS-CoV-2. However, extracting this information from sequences is difficult, as most methods of analyzing viral genomes were developed for smaller data sets. Therefore, my objective was to develop new fast estimators of the number of infections (I) and the rate of migration based on simple features of SARS-CoV-2 phylogenies.

I simulated pathogen evolution using a susceptible-exposed-infectious-recovered (SEIR) model of pathogen spread, reconstructing evolution using CoVizu. For simulations of I, I varied the total number …

Integrating Omim And Intact Data For The Analysis Of Gene-Phenotype Interactions In Complex Diseases: A Linux-Based Computational Tool For Network Analysis, Devin Keane

All Theses

The field of genetics is constantly evolving. New advances in bioinformatics and computational approaches are leading to exciting new developments in our ability to treat and prevent diseases. Computational genetics provides valuable insights into the complex mechanisms and layers of biological communication that shape an organism's phenotype. Understanding these mechanisms is critical to advancing human health.

The study of diseases in genetics requires a comprehensive understanding of the interactions between various biological processes, including gene expression, protein synthesis, RNA, metabolism, and cell-cell communication. To effectively address the root causes of such diseases, multi-disciplinary approaches that integrate information from different levels …

The Genomics Of Autism-Related Genes Il1rapl1 And Il1rapl2: Insights Into Their Cortical Distribution, Cell-Type Specificity, And Developmental Trajectories, Jacob Weaver

MUSC Theses and Dissertations

Neuropsychiatric disorders have a significant impact on modern society. These disorders affect a large percentage of the population: schizophrenia has a world-wide prevalence of 1% and autism spectrum disorders (ASD) affects 1 in 59 school-aged children in the US. There is substantial evidence that most neuropsychiatric disorders have a genetic component. Thus, with the advent of high throughput sequencing much effort has gone into identifying genetic variants associated with these disorders. The emerging picture from these studies is a complex one where hundreds of genes with small effects interact with a varied landscape of common variants to result in disease. …