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Articles 121 - 150 of 400
Full-Text Articles in Computational Biology
Comparative Transcriptomic Analysis Of Cancer Testis Genes In Ovarian Cancer, Zayne Knuth
Comparative Transcriptomic Analysis Of Cancer Testis Genes In Ovarian Cancer, Zayne Knuth
Dissertations, Master's Theses and Master's Reports
Cancer testis genes are common targets for the development of immunotherapy for cancer treatment. Ovarian cancer is one of the leading causes of death in women cancer patients. Cancer testis genes play a role in tumorigenesis, but it is not clear how these genes are activated. This study utilized differential expression analysis between The Cancer Genome Atlas (TCGA) ovarian cancer data, Genotype-Tissue Expression (GTEx) non-cancerous ovary and testis data, and cell line data to identify a list of cancer testis genes that have a novel expression profile. To identify ovarian cancer testis genes, we obtained normal ovary tissue data and …
Integrative Analysis Of Multi-Omics Kinome Data And Virtual Screening Of Identified Targets With Pan-Cancer Application, Siddesh Southekal
Integrative Analysis Of Multi-Omics Kinome Data And Virtual Screening Of Identified Targets With Pan-Cancer Application, Siddesh Southekal
Theses & Dissertations
Cancer is a heterogeneous disease characterized by the uncontrolled growth and dissemination of abnormal cells. Unfortunately, it is also challenging to treat due to the heterogeneous nature of the tumors and the lack of known drugs that are effective against all tumor subpopulations.
The human protein kinases represent an essential and diverse family of enzymes and are often dysregulated in cancer. The human kinome comprises only around 2% of all coding genes of the human genome but phosphorylates about 30% of cellular proteins critical for regulating various biological processes such as cell proliferation, cell cycle progression, apoptosis, motility, growth, differentiation, …
Evaluation Of Deep Neural Network Prospr For Accurate Protein Distance Predictions On Casp14 Targets, Jacob A. Stern, Bryce Eric Hedelius, Olivia Fisher, Wendy M. Billings, Dennis Della Corte
Evaluation Of Deep Neural Network Prospr For Accurate Protein Distance Predictions On Casp14 Targets, Jacob A. Stern, Bryce Eric Hedelius, Olivia Fisher, Wendy M. Billings, Dennis Della Corte
Faculty Publications
The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference time for applications that require the folding of hundreds of sequences. The prediction of protein structure annotations, such as amino acid distances, can be achieved at a higher speed with existing tools, such as the ProSPr network. Here, we report on important updates to the ProSPr network, its performance in the recent Critical Assessment of Techniques for Protein Structure Prediction (CASP14) competition, and an evaluation of its …
Improved Radiation Expression Profiling In Blood By Sequential Application Of Sensitive And Specific Gene Signatures, Eliseos J. Mucaki, Ben C. Shirley, Peter K. Rogan
Improved Radiation Expression Profiling In Blood By Sequential Application Of Sensitive And Specific Gene Signatures, Eliseos J. Mucaki, Ben C. Shirley, Peter K. Rogan
Biochemistry Publications
Purpose. Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.
Methods. This study investigated recall by previous and novel radiation signatures independently derived …
Human 5’-Tailed Mirtrons Are Processed By Rnasep, Mohammad Farid Zia
Human 5’-Tailed Mirtrons Are Processed By Rnasep, Mohammad Farid Zia
Dissertations
Approximately a thousand microRNAs (miRNAs) are documented from human cells. A third appear to transit non-canonical pathways that typically bypass processing by Drosha, the dedicated nuclear miRNA producing enzyme. The largest class of non-canonical miRNAs are mirtrons which eschew Drosha to mature through spliceosome activity. While mirtrons are found in several configurations, the vast majority of human mirtron species are 5’-tailed. For these mirtrons, a 3’ splice site defines the 3’ end of their hairpin precursor while a “tail” of variable length separates the 5’ base of the hairpin from the nearest splice site. How this tail is removed is …
In Silico Identification Of A Streptococcus Phage From An Unpasteurized Dairy Product
In Silico Identification Of A Streptococcus Phage From An Unpasteurized Dairy Product
Symposium of Student Scholars
This study aimed to identify novel phages from a West African dairy product, nunu, to better understand the uncharacterized virosphere of a food microbiome. Nunu is a yogurt-like product from spontaneous fermentation of unpasteurized cow milk without a standardized starter culture. Phages and their bacterial hosts make up a microbiome, where their collective metagenome can be studied in silico, or computationally, after next generation sequencing (NGS). The targeted dataset for our study can be found in the Sequence Read Archives under the accession number of ERX2041567. This study utilized several bioinformatics software tools with customized settings: Kraken2, MetaVelvet, Edena, NCBI-BLAST, …
In Silico Isolation Of A Novel Phage For Food Safety Applications Against Pathogenic E. Coli, Daisy Mcgrath
In Silico Isolation Of A Novel Phage For Food Safety Applications Against Pathogenic E. Coli, Daisy Mcgrath
Symposium of Student Scholars
With the advent of next-generation sequencing (NGS) on metagenomes, the elucidation of all genetic material from microbiomes has prompted a renewed interest towards uncultivated members of the virosphere. We describe the discovery of a novel phage from a metagenomic dataset on the West African fermented dairy product, nunu, with a custom bioinformatics workflow to potentially serve as a biocontrol agent against pathogenic E. coli. Initial dataset of ERR2014814 from NCBI was first subjected to Kraken2 to extract novel sequencing reads for further de novo assembly into contigs by MetaVelvet. Resultant contigs served as potential partial phage genomes, then searched …
Drug Repurposing For Covid-19 Using Molecular Docking Tools, Deniz Yasar Oztas
Drug Repurposing For Covid-19 Using Molecular Docking Tools, Deniz Yasar Oztas
Computational and Data Sciences (MS) Theses
Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious and mortal, finding a treatment is time critical. Drug repurposing is probably the quickest and safest approach in our arsenal. However, testing every drug in a brute force manner would require a lot of resources, and a more sophisticated method is required to filter possible candidates. Since several molecules have already been shown to be effective against SARS-CoV-2 in wet-lab experiments, choosing drugs with similar characteristics would increase our chances of success. In this study, we compare the molecular docking results of FDA-approved drugs from the ZINC database against …
Unveiling Global Roles Of G-Quadruplexes And G4-22 In Human Genetics, Ruth Barros De Paula
Unveiling Global Roles Of G-Quadruplexes And G4-22 In Human Genetics, Ruth Barros De Paula
Dissertations and Theses (Open Access)
G-quadruplexes are non-B DNA structures formed by four or more runs of repeated guanines that confer unique features to living organism’s genomes. These sequences are enriched in regulatory regions, such as promoters and 5’ UTRs, and have distinct regulatory roles in both health and disease states. Even though previous studies showed the impact of G4 in gene expression, none of them summarized the location-specific effect of G4. Also, there is no broad understanding about the most common G4 repeat in the human genome, named here as G4-22, and how it links to the evolution of mammals and their biology. In …
Characterization Of The Growth Factor Receptor Network Oncogenes In Lung Cancer, Ashley Duche
Characterization Of The Growth Factor Receptor Network Oncogenes In Lung Cancer, Ashley Duche
Pharmaceutical Sciences (MS) Theses
Lung cancer remains the leading cause of cancer related deaths worldwide, reportedly contributing to 1.8 million of the 10.0 million mortalities documented in the year 2020. Although advancements have been made in therapeutics and diagnostic methods, formulation of effective treatments and development of drug resistance continues to be a challenge. These challenges arise from our lack of understanding of intricate signaling pathways, such as the Growth Factor Receptor Network (GFRN), which contributes to complex lung tumor heterogeneity allowing for drug resistance development. In this study, gene expression signatures of six GFRN oncogenes overexpressed in human mammary epithelial cells (HMECs) were …
Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha
Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha
LSU Doctoral Dissertations
Schrenkiella parvula is an extremophyte model closely related to Arabidopsis thaliana and Brassica crops. Its natural habitat includes shores of saline lakes in the Irano-Turanian region. It has adapted to grow in soils rich in multiple salts including Na+ and K+. I have investigated the genetic basis for high K+ tolerance in plants using S. parvula as a stress tolerant model compared to the premier plant model, Arabidopsis thaliana which is highly sensitive to salt stresses using physiological, ionomic, transcriptomic, and metabolomic approaches. Under high K+ stress, root system architecture changes significantly compared to control …
Comparative Genomics Methods And Applications, Emily N. Alden
Comparative Genomics Methods And Applications, Emily N. Alden
Biomedical Sciences ETDs
Virtually all fields of biology have benefited from the advancements in comparative genomics technologies, specifically in the study of evolution. In this dissertation I develop and use comparative genomic technologies to investigate the novel SARS-CoV-2 virus, assembly the first genome of the black lace domestic angelfish and identify germline genetic variants associated with altered breast cancer-specific survival. Our genome tiling array for the novel coronavirus presents a rapid and cost-effective method to sequence the entire viral genome and can be used to track the rapid evolution of viral variants in the population. The domestic angelfish is a member of the …
The Differences Of Prokaryotic Pan-Genome Analysis On Complete Genomes And Simulated Metagenome-Assembled Genomes, Tang Li
Department of Food Science and Technology: Dissertations, Theses, and Student Research
Metagenomic assembly is often used in microbiome research. In metagenomic assembly, contigs are binned based on the shared nucleotide composition. These contig bins are called metagenome-assembled genomes (MAGs), each representing a unique bacterial genome recovered from metagenome sequencing. Hundreds of thousands of high-quality MAGs of various ecological environments have been published since 2017, and increasingly more MAGs are being used in pan-genome analyses where unculturable species or species without reference genomes are studied in microbiome research. However, compared to the traditional pan-genome analysis that uses isolate genomes (from a pure strain isolated from a mixed bacterial population), it is not …
Dynamic Observers For Unknown Populations, Chris Guiver, Nathan Poppelreiter, Richard Rebarber, Brigitte Tenhumberg, Stuart Townley
Dynamic Observers For Unknown Populations, Chris Guiver, Nathan Poppelreiter, Richard Rebarber, Brigitte Tenhumberg, Stuart Townley
Brigitte Tenhumberg Papers
Dynamic observers are considered in the context of structuredpopulation modeling and management. Roughly, observers combine a known measured variable of some process with a model of that process to asymptotically reconstruct the unknown state variable of the model. We investigate the potential use of observers for reconstructing population distributions described by density-independent (linear) models and a class of density-dependent (nonlinear) models. In both the density-dependent and -independent cases, we show, in several ecologically reasonable circumstances, that there is a natural, optimal construction of these observers. Further, we describe the robustness these observers exhibit with respect to disturbances and uncertainty in …
Impact Of Intratumor Heterogeneity And The Tumor Microenvironment In Shaping Tumor Evolution And Response To Therapy, Akash Mitra
Impact Of Intratumor Heterogeneity And The Tumor Microenvironment In Shaping Tumor Evolution And Response To Therapy, Akash Mitra
Dissertations and Theses (Open Access)
Intratumor heterogeneity (ITH) is a crucial challenge in cancer treatment. The genotypic and phenotypic heterogeneity underlying diverse cancer types leads to subclonal variation, which may result in mixed or failed response to therapy. The heterogeneity at the tumor level, along with the tumor microenvironment (TME), often shapes tumor evolution and ultimately clinical outcome. Given that modern treatment paradigms increasingly expose patients with metastatic disease to multiple treatment modalities through the course of their disease, there exists a need to characterize robust and predictive biomarkers of response to therapy. In order to accurately characterize tumor evolution, we need to account for …
Identifying The Cell Composition And Clonal Diversity Of Supratentorial Ependymoma Using Single Cell Rna-Sequencing, James He
University Scholar Projects
Ependymoma is a primary solid tumor of the central nervous system. Supratentorial ependymoma (ST-EPN), a subtype of ependymomas, is driven by an oncogenic fusion between the ZFTA and RELA genes in 70% of cases. We introduced this fusion into neural progenitor cells of mice embryos via in utero electroporation of a non-viral binary piggyBac transposon system containing ZFTA-RELA. From preliminary data in the LoTurco lab, inducing the expression of ZFTA-RELA into different neural progenitor cells produces tumors of varying lethality and cellular composition. To define the cellular composition and subclonal diversity of ST-EPN tumors, we used single cell RNA-sequencing to …
Mucin And Splice Variant Profiles Of Pancreatic Adenocarcinoma Predict Patient Survival And Subtyping, Christopher M. Thompson
Mucin And Splice Variant Profiles Of Pancreatic Adenocarcinoma Predict Patient Survival And Subtyping, Christopher M. Thompson
Theses & Dissertations
PDAC is a pancreatic epithelial malignancy and demonstrates aggressive progression and bleak patient prognosis. Despite decades of research, the evolution of novel diagnostics and intervention modalities for PDAC is stagnant. This dissertation explores the characteristic aberrant and elevated expression of mucins in PDAC. Beginning with the hypothesis that mucins are associated with disease aggressiveness, analysis of PDAC patient survival in TCGA revealed no associations between single mucin expression and patient survival. This led to the underlying issue of PDAC tumor cellularity since this disease demonstrates variability in the proportion of cancer cells within the tumor. Tumor purity assessed with the …
Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede
Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede
Dissertations and Theses (Open Access)
Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …
Computational Approaches To Delineate Transcriptional And Functional Heterogeneity In Pancreatic Cancer, Sanjana Srinivasan
Computational Approaches To Delineate Transcriptional And Functional Heterogeneity In Pancreatic Cancer, Sanjana Srinivasan
Dissertations and Theses (Open Access)
Pancreatic ductal adenocarcinoma (PDAC) is an incurable disease characterized by poor survival, dense desmoplastic stroma and activating mutations in KRAS (>90%). These tumors are highly complex ecosystems composed of molecularly distinct sub-populations that exhibit a spectrum of genetic features and associated phenotypes. Despite recent advances in the transcriptomic characterization of PDAC into at least two tumor subtypes, this alone has been insufficient to define more specific patterns of oncogenic dependency. To fully leverage advancements in next generation sequencing and functional genomics, we have sought to establish computational methodologies to aid in refined target discovery, and to develop a novel …
Rare Variant Association Studies In Crohn’S Disease And Colorectal Cancer: Methods And Applications, Jiun-Sheng Chen
Rare Variant Association Studies In Crohn’S Disease And Colorectal Cancer: Methods And Applications, Jiun-Sheng Chen
Dissertations and Theses (Open Access)
Genetic factors account for a substantial portion of Crohn’s disease and colorectal cancer (CRC) risk. Patients with Crohn’s disease, a condition that causes chronic inflammation of the gastrointestinal tract, are at increased risk of colorectal cancer morbidity and mortality. Genome-wide association studies using single marker approaches have identified loci responsible for these diseases, but disease susceptibility from rare variants is incompletely understood. This dissertation includes three chapters, two association studies for Crohn’s disease and CRC, and a statistical method to improve the power of statistical tests.
For Crohn’s disease, we performed targeted sequencing of 101 genes in 205 children with …
The Whole Is Greater Than Its Parts: Ensembling Improves Protein Contact Prediction, Wendy M. Billings, Connor J. Morris, Dennis Della Corte
The Whole Is Greater Than Its Parts: Ensembling Improves Protein Contact Prediction, Wendy M. Billings, Connor J. Morris, Dennis Della Corte
Faculty Publications
The prediction of amino acid contacts from protein sequence is an important problem, as protein contacts are a vital step towards the prediction of folded protein structures. We propose that a powerful concept from deep learning, called ensembling, can increase the accuracy of protein contact predictions by combining the outputs of different neural network models. We show that ensembling the predictions made by different groups at the recent Critical Assessment of Protein Structure Prediction (CASP13) outperforms all individual groups. Further, we show that contacts derived from the distance predictions of three additional deep neural networks—AlphaFold, trRosetta, and ProSPr—can be substantially …
Insights Into Leptopilina Spp. Immune-Suppressive Strategies Using Mixed-Omics And Molecular Approaches, Brian Wey
Dissertations, Theses, and Capstone Projects
Host-parasite interactions influence the biology of each over the course of evolution. Parasite success allows for the passage of potent virulence strategies from generation to generation. Host success passes stronger immunity and resistance strategies to the following generations as well. Only by studying both partners within their natural contexts can we begin to understand the relationship between the two and how immune mechanisms and virulence strategies interact as a molecular arms race.
In this work, we focus on a natural host-parasite pair, the Drosophila-Leptopilina model. Leptopilina species are parasites of several fruit fly species, including Drosophila melanogaster. This model …
Distribution And Diversity Of Heliothine And Other Lepidopteran Nudiviruses, Emrah Ozel
Distribution And Diversity Of Heliothine And Other Lepidopteran Nudiviruses, Emrah Ozel
Theses and Dissertations--Entomology
Helicoverpa zea nudivirus 2 (HzNV-2) is the only known sterilizing and sexually-transmitted insect virus and causes pathological symptoms in H. zea reproductive tissues. HzNV-2 has features that make it a candidate as a H. zea (corn earworm) control agent, such as the ability to cause asymptomatic (latent) and symptomatic (lytic) infections and the ability to influence mating behavior of its host to favor virus spread. HzNV pathology has been studied and its genome sequenced, however, its prevalence in natural populations is largely unknown. In this study, we developed and used a low-cost PCR-based molecular survey to investigate HzNV-2 prevalence and …
Novel Computational Methods For Cancer Genomics Data Analysis, Jinpeng Liu
Novel Computational Methods For Cancer Genomics Data Analysis, Jinpeng Liu
Theses and Dissertations--Computer Science
Cancer is a genetic disease responsible for one in eight deaths worldwide. The advancement of next-generation sequencing (NGS) technology has revolutionized the cancer research, allowing comprehensively profiling the cancer genome at great resolution. Large-scale cancer genomics research has sparked the needs for efficient and accurate Bioinformatics methods to analyze the data. The research presented in this dissertation focuses on three areas in cancer genomics: cancer somatic mutation detection; cancer driver genes identification and transcriptome profiling on single-cell level.
NGS data analysis involves a series of complicated data transformation that convert raw sequencing data to the information that is interpretable by …
Leveraging Transcriptomic Approaches To Identify Differences In Genetic Programming Driving Two Distinct Wound Healing Mechanisms, Regeneration And Fibrosis, In Acomys And Mus, Shishir K. Biswas
Theses and Dissertations--Biology
Why can some animals and others cannot? This fundamental question has fueled scientists studying regeneration for hundreds of years since early observations in crayfish, salamanders and many other organisms. While most contemporary work in regeneration is done in a handful of species including salamanders, zebrafish and flatforms, these organisms lack a closely-related, non-regenerating sister species from which unique genetic differences can be identified. Additionally, while much has been learned from these organisms, they do not share fundamental biological traits with mammals (endothermy, metabolism and immune system) which limits the ability to translate this research for clinical medicine. To this end, …
Evolution And Clinical Relevance Of Vaginal Bifidobacterium Breve In The Vaginal Environment, Nicole R. Jimenez
Evolution And Clinical Relevance Of Vaginal Bifidobacterium Breve In The Vaginal Environment, Nicole R. Jimenez
Theses and Dissertations
The vaginal microbiome is important in reproductive health and disease and is often dominated by lactobacilli. However, there are many other community state types dominated by single species that are still not well characterized. Bifidobacterium species such as Bifidobacterium breve and Bifidobacterium longum have been observed to dominate vaginal profiles. Bifidobacteria are important in infant gut development, but little is known about their role in vaginal health. Thus, we sought to use a multisystem approach to better characterize Bifidobacterium species present in the vaginal microbiome with an emphasis on B. breve. Eight strains of B. breve were isolated from vaginal …
Sparse Forward-Backward Alignment For Sensitive Database Search With Small Memory And Time Requirements, David H. Rich
Sparse Forward-Backward Alignment For Sensitive Database Search With Small Memory And Time Requirements, David H. Rich
Graduate Student Theses, Dissertations, & Professional Papers
Sequence annotation is typically performed by aligning an unlabeled sequence to a collection of known sequences, with the aim of identifying non-random similarities. Given the broad diversity of new sequences and the considerable scale of modern sequence databases, there is significant tension between the competing needs for sensitivity and speed, with multiple tools displacing the venerable BLAST software suite on one axis or another. In recent years, alignment based on profile hidden Markov models (pHMMs) and associated probabilistic inference methods have demonstrated increased sensitivity due in part to consideration of the ensemble of all possible alignments between a query and …
Ensemble Protein Inference Evaluation, Kyle Lee Lucke
Ensemble Protein Inference Evaluation, Kyle Lee Lucke
Graduate Student Theses, Dissertations, & Professional Papers
The Protein inference problem is becoming an increasingly important tool that aids in the characterization of complex proteomes and analysis of complex protein samples. In bottom-up shotgun proteomics experiments the metrics for evaluation (like AUC and calibration error) are based on an often imperfect target-decoy database. These metrics make the inherent assumption that all of the proteins in the target set are present in the sample being analyzed. In general, this is not the case, they are typically a mix of present and absent proteins. To objectively evaluate inference methods, protein standard datasets are used. These datasets are special in …
Applications Of Machine Learning In Microbial Forensics, Ryan B. Ghannam
Applications Of Machine Learning In Microbial Forensics, Ryan B. Ghannam
Dissertations, Master's Theses and Master's Reports
Microbial ecosystems are complex, with hundreds of members interacting with each other and the environment. The intricate and hidden behaviors underlying these interactions make research questions challenging – but can be better understood through machine learning. However, most machine learning that is used in microbiome work is a black box form of investigation, where accurate predictions can be made, but the inner logic behind what is driving prediction is hidden behind nontransparent layers of complexity.
Accordingly, the goal of this dissertation is to provide an interpretable and in-depth machine learning approach to investigate microbial biogeography and to use micro-organisms as …
Composition And Homology In The Taxonomic Classification Of Escherichia Coli, Tanya Irani
Composition And Homology In The Taxonomic Classification Of Escherichia Coli, Tanya Irani
Theses and Dissertations (Comprehensive)
As new techniques have been introduced, specifically the possibility of complete genome sequencing, better methods of defining bacterial species have also been proposed. One of the most recently proposed methods, using bioinformatic techniques, is to calculate the average nucleotide identity (ANI) between the homologous genome segments of different isolates. Another method for species discrimination that has been tested successfully is the similarity of DNA compositional signatures. However, in a recent update, DNA signatures split the available Escherichia coli complete genomes into three groups. To check if this result was consistent with such genomes belonging to different species, we tested methods …