Bioinformatics Commons^™

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

From Formulas To Futures: Mathematical Insights Into Endosomal Escape, Fnu Nisha

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Inverse Probability Weighting In Survival Analysis And Network Analysis, Yukun Lu

Doctoral Dissertations

Inverse probability weighting is a popular technique to accommodate selection bias due to non-random sampling and missing data. In the first chapter, we develop an inverse probability weighted estimator and an augmented inverse probability weighted estimator of regression coefficients for a linear model with randomly censored covariates, when the censoring mechanism may be dependent on the outcome. We investigate the asymptotic properties of both estimators and evaluate their finite sample performance through extensive simulation studies. We apply the proposed methods to an Alzheimer’s disease study. In the second chapter, we present an application of network analysis in a study of …

Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao

Dissertations, Master's Theses and Master's Reports

This dissertation includes five Chapters. A brief description of each chapter is organized as follows.

In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.

In Chapter Two, we first illustrate the proposed GPN …

Dynamics Of Redox-Driven Molecular Processes In Local And Systemic Plant Immunity, Philip Berg

Theses and Dissertations

The work here presents two main parts. In the first part, chapters 1 – 3 focus on dynamical systems modeling in plant immunity, whereas chapters 4 – 6 describe contributions to computational modeling and analysis of proteomics and genomics data. Chapter 1 investigates dynamical and biochemical patterns of reversibly oxidized cysteines (RevOxCys) during effector-triggered immunity (ETI) in Arabidopsis, examines the regulatory patterns associated with Arabidopsis thimet oligopeptidase 1 and 2’s (TOP1 and TOP2), roles in the RevOxCys events during ETI, and analyzes the redox phenotype of the top1top2 mutant. The second chapter investigates the peptidome dynamics during ETI …

Comparative Transcriptomic Study Between Cyanobacteria That Contain Chlorophyll D And Those That Lack Chlorophyll D, Fernanda Montoya

Honors Capstones

All cyanobacteria, which perform oxygenic photosynthesis on Earth, contain the photosynthetic pigment chlorophyll a (Chl a) that absorbs light in the violet and red region of the visible spectrum. Cyanobacteria of the Acaryochloris species, however, contain the rare photosynthetic pigment chlorophyll d (Chl d) that absorbs light in the far-red region. Chl d’s ability to absorb light in this region allows it to avoid competing with other photosynthetic organisms for light. Creating a photosystem that uses Chl d in plants would be of great use for agricultural land optimization, but requires knowledge of the biosynthetic pathways of …

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 …

Upregulation Of Cd36, A Fatty Acid Translocase, Promotes Colorectal Cancer Metastasis By Increasing Mmp28 And Decreasing E-Cadherin Expression, James Drury, Piotr G. Rychahou, Courtney O. Kelson, Mariah E. Geisen, Yuanyuan Wu, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Yekaterina Y. Zaytseva

Surgery Faculty Publications

Altered fatty acid metabolism continues to be an attractive target for therapeutic intervention in cancer. We previously found that colorectal cancer (CRC) cells with a higher metastatic potential express a higher level of fatty acid translocase (CD36). However, the role of CD36 in CRC metastasis has not been studied. Here, we demonstrate that high expression of CD36 promotes invasion of CRC cells. Consistently, CD36 promoted lung metastasis in the tail vein model and GI metastasis in the cecum injection model. RNA-Seq analysis of CRC cells with altered expression of CD36 revealed an association between high expression of CD36 and upregulation …

Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee

Theses and Dissertations

Primary Care is on the frontlines of healthcare, thus they see the most diverse set of patients. In order to achieve high functioning primary care, a practice must establish empanelment, the pairing of patients to providers. Enumeration of empanelment, or estimating panel sizes, helps ensure that the demands of the patients demand the supply of providers and optimize the balance of primary care resources to improve quality of care. Further we can adjust panel sizes by using patient-level data on healthcare utilization and complexity extracted from the electronic medial record to determine the amount of care or burden of work …

Framework For The Evaluation Of Perturbations In The Systems Biology Landscape And Inter-Sample Similarity From Transcriptomic Datasets — A Digital Twin Perspective, Mariah Marie Hoffman

Dissertations and Theses

One approach to interrogating the complexities of human systems in their well-regulated and dysregulated states is through the use of digital twins. Digital twins are virtual representations of physical systems that are descriptive of an individual's state of health, an object fundamentally related to precision medicine. A key element for building a functional digital twin type for a disease or predicting the therapeutic efficacy of a potential treatment is harmonized, machine-parsable domain knowledge. Hypothesis-driven investigations are the gold standard for representing subsystems, but their results encompass a limited knowledge of the full biosystem. Multi-omics data is one rich source of …

Genetic Contributors Of Incident Stroke In 10,700 African Americans With Hypertension: A Meta-Analysis From The Genetics Of Hypertension Associated Treatments And Reasons For Geographic And Racial Differences In Stroke Studies, Nicole D. Armstrong, Vinodh Srinivasasainagendra, Amit Patki, Rikki M. Tanner, Bertha A. Hidalgo, Hemant K. Tiwari, Nita A. Limdi, Ethan M. Lange, Leslie A. Lange, Donna K. Arnett, Marguerite R. Irvin

Epidemiology and Environmental Health Faculty Publications

Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals.

Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs …

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru

Institute for Biomedical Informatics Faculty Publications

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS: The Human Phenotype Ontology …

Verrucous Carcinoma Of The Vulva: Patterns Of Care And Treatment Outcomes., Sara M. Dryden, Leonid B. Reshko, Jeremy T. Gaskins, Scott R. Silva

Faculty Scholarship

Background: Verrucous vulvar carcinoma (VC) is an uncommon and distinct histologic subtype of squamous cell carcinoma (SCC). The available literature on VC is currently limited to case reports and small single institution studies. Aims: The goals of this study were to analyze data from the National Cancer Database (NCDB) to quantitate the incidence of VC and to investigate the effects of patient demographics, tumor characteristics, and treatment regimens on overall survival (OS) in women with verrucous vulvar carcinoma. Methods and results: Patients diagnosed with vulvar SCC or VC between the years of 2004 and 2016 were identified in the NCDB. …

Monitoring Mammals At Multiple Scales: Case Studies From Carnivore Communities, Kadambari Devarajan

Doctoral Dissertations

Carnivores are distributed widely and threatened by habitat loss, poaching, climate change, and disease. They are considered integral to ecosystem function through their direct and indirect interactions with species at different trophic levels. Given the importance of carnivores, it is of high conservation priority to understand the processes driving carnivore assemblages in different systems. It is thus essential to determine the abiotic and biotic drivers of carnivore community composition at different spatial scales and address the following questions: (i) What factors influence carnivore community composition and diversity? (ii) How do the factors influencing carnivore communities vary across spatial and temporal …

A Network-Based Approach For Computational Drug Repurposing On Cancer Data, Ann Reba, Thomas Alexander

Electronic Theses and Dissertations

In this thesis, we are interested in finding the best drugs that can be repurposed for the disease and able to find the adverse effects such drugs that are FDA-Approved. Developing an effective drug can be a time-consuming and expensive crucible method. Network-based machine learning methods are used for predicting a given drug for A that can be used for B. It aims at finding new indications for already existing drugs and therefore increases the available therapeutic choices at a fraction of the cost of new drug development. The perturbation gene expression data corresponding to the MCF7 cell line was …

Pattern Of Use Of Electronic Health Record (Ehr) Among The Chronically Ill: A Health Information National Trend Survey (Hints) Analysis, Rose Calixte, Sumaiya Islam, Zainab Toteh Osakwe, Argelis Rivera, Marlene Camacho-Rivera

Publications and Research

Effective patient–provider communication is a cornerstone of patient-centered care. Patient portals provide an effective method for secure communication between patients or their proxies and their health care providers. With greater acceptability of patient portals in private practices, patients have a unique opportunity to manage their health care needs. However, studies have shown that less than 50% of patients reported accessing the electronic health record (EHR) in a 12-month period. We used HINTS 5 cycle 1 and cycle 2 to assess disparities among US residents 18 and older with any chronic condition regarding the use of EHR for secure direct messaging …

Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil

Open Access Theses & Dissertations

With the rise of high throughput technologies in biomedical research, large volumes of expression profiling, methylation profiling, and RNA-sequencing data are being generated. These high-dimensional data have large number of features with small number of samples, a characteristic called the "curse of dimensionality." The selection of optimal features, which largely affects the performance of classification algorithms in machine learning models, has led to challenging problems in bioinformatics analyses of such high-dimensional datasets. In this work, I focus on the design of two-stage frameworks of feature selection and classification and their applications in multiple sets of colorectal cancer data. The first …

Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook

Undergraduate Research and Scholarship Symposium

Single-nucleotide polymorphisms (SNPs) are variations in the genome where one base pair can differ between individuals.¹ SNPs occur throughout the genome and can correlate to a disease-state if they occur in a functional region of DNA.¹According to the central dogma of molecular biology, any variation in the DNA sequence will have a direct effect on the RNA sequence and will potentially alter the identity or conformation of a protein product. A single RNA molecule, due to intramolecular base pairing, can acquire a plethora of 3-D conformations that are described by its structural ensemble. One SNP, rs12477830, which …

Taxonomic Annotation Of Near-Coral Seawater Microbiota In Kilifi, Kenya, Megan Ruoff

Independent Study Project (ISP) Collection

The general objective of this study was to analyze the microbiome of seawater above a coral reef in Kilifi, Kenya. Specific objectives included establishing a baseline microbiota profile, classifying the identified organisms at various taxonomic levels, and conjecturing about reef health from the presence or absence of bioindicator species including Vibrio bacteria. Sequenced 16S rRNA gene sequences from seawater samples at Kuruwitu Conservancy in Kilifi, Kenya were taxonomically classified by exact matching employing the Dada2 software package and the naïve Bayesian classifier method with 97% similarity cut off. The seawater microbiota contained mostly Proteobacteria (73.28%), followed by Bacteroidetes (14.08%) and …

Real World Clinicopathologic Observations Of Patients With Metastatic Solid Tumors Receiving Immune Checkpoint Inhibitor Therapy: Analysis From Kentucky Cancer Registry, Aasems Jacob, Jianrong Wu, Jill M. Kolesar, Eric B. Durbin, Aju Mathew, Susanne Arnold, Aman Chauhan

Biostatistics Faculty Publications

The state of Kentucky has the highest cancer incidence and mortality in the United States. High‐risk populations such as this are often underrepresented in clinical trials. The study aims to do a comprehensive analysis of molecular landscape of metastatic cancers among these patients with detailed evaluation of factors affecting response and outcomes to immune checkpoint inhibitor (ICI) therapy. We performed a retrospective analysis of metastatic solid tumor patients who received ICI and underwent molecular profiling at our institution.

Sixty nine patients with metastatic solid tumors who received ICI were included in the study. Prevalence of smoking and secondhand tobacco exposure …

A Bayesian Hierarchical Mixture Model With Continuous-Time Markov Chains To Capture Bumblebee Foraging Behavior, Max Thrush Hukill

Honors Projects

The standard statistical methodology for analyzing complex case-control studies in ethology is often limited by approaches that force researchers to model distinct aspects of biological processes in a piecemeal, disjointed fashion. By developing a hierarchical Bayesian model, this work demonstrates that statistical inference in this context can be done using a single coherent framework. To do this, we construct a continuous-time Markov chain (CTMC) to model bumblebee foraging behavior. To connect the experimental design with the CTMC, we employ a mixture model controlled by a logistic regression on the two-factor design matrix. We then show how to infer these model …

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 …

The Causes And Control Measures Of Extended Spectrum Beta-Lactamase Producing Enterobacteriaceae In Long-Term Care Facilities, Ismaila Olatunji Sule

Walden Dissertations and Doctoral Studies

Due to extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE), infections among residents are increasing in long-term care facilities (LTCFs), resulting in high rate of morbidity and healthcare costs. ESBL-PE resists empirical antibiotics and reduces treatment options, and a designated infection control team is unavailable to prevent the prevalence of the disease. Ecological theory guided this study. A systematic review and meta-analysis were conducted to characterize the causes of ESBL-PE and evaluate the infection control strategies within LTCFs. Multiple regression analysis (MRA) was included as supplementary statistical analysis to identify relationships between LTCFs, geographical locations, infection control measures (ICMs), and ESBL-PE. A systematic search …

Impact Of Case Management On Childhood Lead Exposure In Marion County, Indiana, Maliki Yacouba

Walden Dissertations and Doctoral Studies

The Centers for Disease Control and Prevention recently declared that no amount of childhood blood lead level (BLL) is safe. The purpose of this quantitative study with a retrospective cohort design was to evaluate the effectiveness of case management intervention on children diagnosed with elevated BLL (EBLL; ≥ 5 μg/dL) in Marion, County, Indiana. The health belief model was used as the theoretical foundation for the study. A data set of 160 lead exposure case management records was analyzed to find whether: (a) BLL at post-case-management time significantly differ from BLL at baseline (b) BLL at post-case-management time is affected …

Gene Set Testing By Distance Correlation, Sho-Hsien Su

Graduate Theses and Dissertations

Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess the …

Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das

Electronic Theses and Dissertations

Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …

Modified-Half-Normal Distribution And Different Methods To Estimate Average Treatment Effect., Jingchao Sun

Electronic Theses and Dissertations

This dissertation consists of three projects related to Modified-Half-Normal distribution and causal inference. In my first project, a new distribution called Modified-Half-Normal distribution was introduced. I explored a few of its distributional properties, the procedures for generating random samples based on Bayesian approaches, and the parameter estimation based on the method of moments. The second project deals with the problem of selection bias of average treatment effect (ATE) if we use the observational data. I combined the propensity score based inverse probability of treatment weighting (IPTW) method and the directed acyclic graph (DAG) to solve this problem. The third project …

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 …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …

Multi-Omics Integration For Gene Fusion Discovery And Somatic Mutation Haplotyping In Cancer, Steven Mason Foltz

Arts & Sciences Electronic Theses and Dissertations

Cancer is a disease caused by changes to the genome and dysregulation of gene expression. Among many types of mutations, including point mutations, small insertions and deletions, large scale structural variants, and copy number changes, gene fusions are another category of genomic and transcriptomic alteration that can lead to cancer and which can serve as therapeutic targets. We studied gene fusion events using data from The Cancer Genome Atlas, including over 9,000 patients from 33 cancer types, finding patterns of gene fusion events and dysregulation of gene expression within and across cancer types. With data from the CoMMpass study (Multiple …