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Full-Text Articles in Medical Biomathematics and Biometrics

Network Analysis: An Application Of Graph Theory In Biology, Kiana Dunbar Apr 2026

Network Analysis: An Application Of Graph Theory In Biology, Kiana Dunbar

Honors Theses

Graphs are simple, visual representations of entities as nodes connected by edges. They are used to convey relationships within a system. Networks are comprised of interrelated entities that are not easily separable, producing complex, structured data. These can be seen in social groups, highway systems, and even in biological systems. This paper surveys concepts in graph theory for application to the analysis of network data to understand disease. The features of graphs provide a useful framework for thinking about relationships between different genes or proteins. The structure of graphs is also compatible with a variety of machine learning tools. Especially …


Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev Jan 2026

Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev

Theses and Dissertations

Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level Dcrit = (rS - rR)/(dS - dR) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …


A Bayesian Late-Fusion Supportability Framework For Rare-Disease Severity Prediction In Glut1 Deficiency Syndrome, Jordan M. Rodriguez Jan 2026

A Bayesian Late-Fusion Supportability Framework For Rare-Disease Severity Prediction In Glut1 Deficiency Syndrome, Jordan M. Rodriguez

Mathematics Dissertations

Glucose transporter type 1 deficiency syndrome (GLUT1-DS) is a rare neurometabolic disorder with heterogeneous neurological and developmental severity. Because patient-level severity is not observed as a single validated outcome, this dissertation develops a Bayesian late-fusion supportability framework for constructing and predicting an ordered latent severity phenotype from clinical, genetic, and EEG-derived evidence. The primary target was constructed in a larger clinical cohort using age-5 symptom burden and learning cognition, then assigned to an aligned multimodal prediction cohort. Target-defining variables were excluded from supervised predictors, and models were evaluated using patient-exclusive cross-validation with training-fold preprocessing and fold-wise EEG PCA.

The primary …


An Exposition On Prostate Cancer Dynamics: A History And Exploration Of Cancer Growth Models, Walter Navarro May 2025

An Exposition On Prostate Cancer Dynamics: A History And Exploration Of Cancer Growth Models, Walter Navarro

Electronic Theses, Projects, and Dissertations

The detection, diagnosis, and treatment of cancer are the primary objectives of the field of mathematical oncology. Our goal is to examine the history of mathematical oncology by introducing the models that have influenced it. From this vantage point, we examine five primary models that focus on the progression of prostate cancer and the development of treatment protocols at different stages. The Ideta model will be further elaborated upon by examining the effects of androgen deprivation therapy and the addition of chemotherapy on growth dynamics. Finally, clinical data will be utilized to verify the Vollmer and Humphrey model’s findings. We …


Genetic Analysis Of Hereditary Gingival Fibromatosis Associated Sos1 Missense Variants Of Uncertain Significance In Caenorhabditis Elegans, Himani Patel Apr 2024

Genetic Analysis Of Hereditary Gingival Fibromatosis Associated Sos1 Missense Variants Of Uncertain Significance In Caenorhabditis Elegans, Himani Patel

Theses

Hereditary gingival fibromatosis (HGF) is a disease that can present as benign overgrowth of gingival tissue in the mouth. The overgrowth can enclose the entire mouth and teeth in severe cases or present itself in a concentrated area. Researchers have identified that mutations in the SOS1 gene can be responsible for HGF. This disease can impair basic functions related to the mouth. Eating, smiling, speaking can all be affected. Additionally, excess inflammation can cause periodontal disease because of the difficulty in maintaining proper oral health. Periodontal disease can lead to severe bone loss which can lead to complete loss of …


Effect Of Specific Data Variations On Automated Speaker Recognition, Ethan David Meighen Jan 2024

Effect Of Specific Data Variations On Automated Speaker Recognition, Ethan David Meighen

Graduate Theses, Dissertations, and Problem Reports (ETD)

Speaker recognition is not a new biometric modality but there are still many obstacles in the way in order for it to become as used as fingerprint recognition, facial recognition, and iris recognition. Many real-world environmental conditions, hardware device variations, and human behavior present serious challenges to the use of opportunistic voice or speaker samples for identification purposes. Non-idealities, identified as nuisance factors, include environmental noise, input device quality, length of utterance, sample rate variation, and unscripted data are common nuisance factors that can impact speaker recognition match score performance. The impact of the nuisance factors listed above were evaluated …


A Class Of Game-Theoretic And Fokker-Planck Optimal Control Frameworks In Colon And Esophageal Cancer, Mesfer Alajmi Phd Jan 2024

A Class Of Game-Theoretic And Fokker-Planck Optimal Control Frameworks In Colon And Esophageal Cancer, Mesfer Alajmi Phd

Mathematics Dissertations - Archive

In this dissertation, we first present a new stochastic framework for parameter estimation and uncertainty quantification in colon cancer-induced immune responses. A stochastic process that captures the system's inherent randomness determines the dynamics of colon cancer. The stochastic framework is based on the Fokker-Planck equation, which represents the evolution of the probability density function corresponding to the stochastic process. We formulate an optimization problem that takes individual patient data with randomness present and solves it to obtain the unknown parameters corresponding to the individual tumor characteristics. Furthermore, we perform a sensitivity analysis of the optimal parameter set to identify the …


Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile May 2023

Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile

Statistical Science Theses and Dissertations

Tumor xenograft experiments are a popular tool of cancer biology research. In a typical such experiment, one implants a set of animals with an aliquot of the human tumor of interest, applies various treatments of interest, and observes the subsequent response. Efficient analysis of the data from these experiments is therefore of utmost importance. This dissertation proposes three methods for optimizing cancer treatment and data analysis in the tumor xenograft context. The first of these is applicable to tumor xenograft experiments in general, and the second two seek to optimize the combination of radiotherapy with immunotherapy in the tumor xenograft …


Computer-Aided Drug Discovery For Helicobacter Pylori, Nicole Ann Vita Dec 2022

Computer-Aided Drug Discovery For Helicobacter Pylori, Nicole Ann Vita

Theses and Dissertations (ETD)

Helicobacter pylori is a high-priority drug-resistant pathogen and is currently the only bacteria considered to be a class I carcinogen and there is a critical need to identify novel chemical matter to treat H. pylori infections. Hp is responsible for greater than 60% of gastric cancer related deaths and 89% of all gastric cancer morbidities. In a previous study, our lab identified novel Hp thienopyrmidine inhibitors that target respiratory complex I, an essential enzyme in respiration. Respiratory complex I is a large asymmetric multidomain and membrane bound enzyme and due to these innate features, it is not practical for biophysical …


Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte Jan 2022

Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte

Theses and Dissertations

Inverse modeling in cardiovascular medicine is a collection of methodologies that can provide non-invasive patient-specific estimations of clinical risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs.

Herein, three different phase contrast magnetic resonance imaging (MRI) modalities were implemented as input data, displacement encoding with stimulated echoes (DENSE MRI) applied, and time-resolved velocity encoding phase-contrast MRI, in 1D and 3D, applied to pulmonary artery (PA) hemodynamics.

A model to account for the effect of periaortic interactions due to static and dynamic structures …


Quantifying The Heterogeneity Of The Immunoglobulin G N-Glycome In An Ageing Australian Population: The Busselton Healthy Ageing Study, Alyce Russell Jan 2020

Quantifying The Heterogeneity Of The Immunoglobulin G N-Glycome In An Ageing Australian Population: The Busselton Healthy Ageing Study, Alyce Russell

Theses: Doctorates and Masters

The use of immunoglobulin G N-glycomics to study chronic non-communicable disorders and other complex phenotypes emerged following the Human Genome Project. The consortium discovered that most phenotypes were too complex to be explained by genetics alone. Thus, the biological importance of epigenetics was recognised; heritable modifications to gene expression rather than the genome itself. Nglycosylation is a form of epigenetic regulation known as a post-translational modification. It stabilises the immunoglobulin G structure and alters downstream responses elicited by the antibody and is extensively studied as a candidate biomarker in the post-genomic era.

The N-glycosylation of immunoglobulin G itself is complex, …


Deepcon-Pre: Improved Protein Contact Map Prediction Using Inverse Covariance And Deep Residual Networks, Nachammai Palaniappan Oct 2019

Deepcon-Pre: Improved Protein Contact Map Prediction Using Inverse Covariance And Deep Residual Networks, Nachammai Palaniappan

Theses

As with most domains where machine learning methods are applied, correct feature engineering is critical when developing deep learning algorithms for solving the protein folding problem. Unlike the domains such as computer vision and natural language processing, feature engineering is not rigorously studied towards solving the protein folding problem. A recent research has highlighted that input features known as precision matrix are most informative for predicting inter-residue contact map, the key for building three-dimensional models. In this work, we study the significance of the precision matrix feature when very deep residual networks are trained. Using a standard dataset of 3456 …


Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor Aug 2018

Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor

Electronic Theses and Dissertations

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …


Flexor Dysfunction Following Unilateral Transient Ischemic Brain Injury Is Associated With Impaired Locomotor Rhythmicity, Kiril Tuntevski Jan 2018

Flexor Dysfunction Following Unilateral Transient Ischemic Brain Injury Is Associated With Impaired Locomotor Rhythmicity, Kiril Tuntevski

Graduate Theses, Dissertations, and Problem Reports (ETD)

Functional motor deficits in hemiplegia after stroke are predominately associated with flexor muscle impairments in animal models of ischemic brain injury, as well as in clinical findings. Rehabilitative interventions often employ various means of retraining a maladapted central pattern generator for locomotion. Yet, holistic modeling of the central pattern generator, as well as applications of such studies, are currently scarce. Most modeling studies rely on cellular neural models of the intrinsic spinal connectivity governing ipsilateral flexor-extensor, as well as contralateral coupling inherent in the spinal cord. Models that attempt to capture the general behavior of motor neuronal populations, as well …


Detecting And Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer To Predict Patient Outcomes, Xenia J. Fave May 2017

Detecting And Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer To Predict Patient Outcomes, Xenia J. Fave

Dissertations and Theses (Open Access)

The purpose of this study was to investigate whether radiomics features measured from weekly 4-dimensional computed tomography (4DCT) images of non-small cell lung cancers (NSCLC) change during treatment and if those changes are prognostic for patient outcomes or dependent on treatment modality. Radiomics features are quantitative metrics designed to evaluate tumor heterogeneity from routine medical imaging. Features that are prognostic for patient outcome could be used to monitor tumor response and identify high-risk patients for adaptive treatment. This would be especially valuable for NSCLC due to the high prevalence and mortality of this disease.

A novel process was designed to …


Mathematical Models Of The Inflammatory Response In The Lungs, Sarah B. Minucci Jan 2017

Mathematical Models Of The Inflammatory Response In The Lungs, Sarah B. Minucci

Theses and Dissertations

Inflammation in the lungs can occur for many reasons, from bacterial infections to stretch by mechanical ventilation. In this work we compare and contrast various mathematical models for lung injuries in the categories of acute infection, latent versus active infection, and particulate inhalation. We focus on systems of ordinary differential equations (ODEs), agent-based models (ABMs), and Boolean networks. Each type of model provides different insight into the immune response to damage in the lungs. This knowledge includes a better understanding of the complex dynamics of immune cells, proteins, and cytokines, recommendations for treatment with antibiotics, and a foundation for more …


Assessing The Potential Clinical Impact Of Variable Biological Effectiveness In Proton Radiotherapy, Christopher R. Peeler Ph.D. Dec 2016

Assessing The Potential Clinical Impact Of Variable Biological Effectiveness In Proton Radiotherapy, Christopher R. Peeler Ph.D.

Dissertations and Theses (Open Access)

It has long been known that proton radiotherapy has an increased biological effectiveness compared to traditional x-ray radiotherapy. This arises from the clustered nature of DNA damage produced by the energy deposition of protons along their tracks in medium. This effect is currently quantified in clinical settings by assigning protons a relative biological effectiveness (RBE) value of 1.1 corresponding to 10% increased effectiveness compared to photon radiation. Numerous studies have shown, however, that the RBE value of protons is variable and can deviate substantially from 1.1, but experimental data on RBE and clinical evidence of its variability remains limited.

The …


The Effects Of Scarring On Face Recognition, Kevin J. Chan Aug 2016

The Effects Of Scarring On Face Recognition, Kevin J. Chan

Open Access Theses

The focus of this research is the effects of scarring on face recognition. Face recognition is a common biometric modality implemented for access control operations such as customs and borders. The recent report from the Special Group on Issues Affecting Facial Recognition and Best Practices for their Mitigation highlighted scarring as one of the emerging challenges. The significance of this problem extends to the ISO/IEC and national agencies are researching to enhance their intelligence capabilities. Data was collected on face images with and without scars, using theatrical special effects to simulate scarring on the face and also from subjects that …


Snpredict: A Machine Learning Approach For Detecting Low Frequency Variants In Cancer, Vatsal Mehra Jul 2016

Snpredict: A Machine Learning Approach For Detecting Low Frequency Variants In Cancer, Vatsal Mehra

Master's Theses (2009 -)

Cancer is a genetic disease caused by the accumulation of DNA variants such as single nucleotide changes or insertions/deletions in DNA. DNA variants can cause silencing of tumor suppressor genes or increase the activity of oncogenes. In order to come up with successful therapies for cancer patients, these DNA variants need to be identified accurately. DNA variants can be identified by comparing DNA sequence of tumor tissue to a non-tumor tissue by using Next Generation Sequencing (NGS) technology. But the problem of detecting variants in cancer is hard because many of these variant occurs only in a small subpopulation of …


Strategies Of Balancing: Regulation Of Posture As A Complex Phenomenon, Allison Leich Hilbun May 2016

Strategies Of Balancing: Regulation Of Posture As A Complex Phenomenon, Allison Leich Hilbun

Electronic Theses and Dissertations

The complexity of the interface between the muscular system and the nervous system is still elusive. We investigated how the neuromuscular system functions and how it is influenced by various perturbations. Postural stability was selected as the model system, because this system provides complex output, which could indicate underlying mechanisms and feedback loops of the neuromuscular system. We hypothesized that aging, physical pain, and mental and physical perturbations affect balancing strategy, and based on these observations, we constructed a model that simulates many aspects of the neuromuscular system. Our results show that aging changes the control strategy of balancing from …


Mathematical Modeling Of Blood Coagulation, Joana L. Perdomo Jan 2016

Mathematical Modeling Of Blood Coagulation, Joana L. Perdomo

HMC Senior Theses

Blood coagulation is a series of biochemical reactions that take place to form a blood clot. Abnormalities in coagulation, such as under-clotting or over- clotting, can lead to significant blood loss, cardiac arrest, damage to vital organs, or even death. Thus, understanding quantitatively how blood coagulation works is important in informing clinical decisions about treating deficiencies and disorders. Quantifying blood coagulation is possible through mathematical modeling. This review presents different mathematical models that have been developed in the past 30 years to describe the biochemistry, biophysics, and clinical applications of blood coagulation research. This review includes the strengths and limitations …


Power Analysis In Applied Linear Regression For Cell Type-Specific Differential Expression Detection, Edmund Glass Jan 2016

Power Analysis In Applied Linear Regression For Cell Type-Specific Differential Expression Detection, Edmund Glass

Theses and Dissertations

The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from any tissues suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. However, this variability may actually be advantageous, as heterogeneous gene expression measurements coupled with cell counts may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression. Yet, they do not consider many artifacts hidden in high-dimensional gene expression …


An Association Study Between Adult Blood Pressure And Time To First Cardiovascular Disease, Yongjia Pu Jan 2015

An Association Study Between Adult Blood Pressure And Time To First Cardiovascular Disease, Yongjia Pu

Theses and Dissertations

BACKGROUND: Several studies have demonstrated the association between the time to hypertension event and multiple baseline measurements for adults, yet other survival cardiovascular disease (CVD) outcomes such as high cholesterol and heart attack have been somewhat less considered. The Fels Longitudinal Study (FLS) provides us an opportunity to connect adult blood pressure (BP) at certain ages to the time to first CVD outcomes. The availability of long-term serial BP measurements from FLS also potentially allows us to evaluate if the trend of the measured BP biomarkers over time predicts survival outcomes in adulthood through statistical modeling.

METHODS: When the reference …


Tibial Tubercle Transfer To Correct Bilateral Patellar Tendinopathy In A Collegiate Football Player, Andrew D. Hamstra Dec 2013

Tibial Tubercle Transfer To Correct Bilateral Patellar Tendinopathy In A Collegiate Football Player, Andrew D. Hamstra

Boise State University Theses and Dissertations

Objective: To present a case of a competitive football player with chronic patellar tendinopathy and the associated bilateral tibial tubercle transfer surgeries performed leading to the reduction of pain and return to participation.

Background: A 19 year-old male football athlete (height= 187.96 cm, mass= 112.037 kg) presented with chronic patellar tendinopathy that began in his high school career and continued to worsen with the increased physical demands associated with participation in collegiate sport.

Differential Diagnosis: Chondromalacia patella and Osgood Schlatters disease.

Treatment: After nonsurgical intervention resulted in no decrease of pain, bilateral tibial tubercle transfer surgery was conducted to correct …


Estimating The Impact Of Lost To Follow-Up On Breast Cancer Patients' Disease-Free Survival, Debbie Yan Qun Huang May 2013

Estimating The Impact Of Lost To Follow-Up On Breast Cancer Patients' Disease-Free Survival, Debbie Yan Qun Huang

Statistics

Background The 5-year survival rate for patients with breast cancer is much higher than patients with other types of cancer. Due to this longer survival period, breast cancer patients also tend to have increased rates of lost to follow-up, when compared to other cancers. When a patient becomes lost, the occurrence of distant metastasis cannot be reliably ascertained, unless the patient had a breast cancer-specific (BC) death. The impact of lost patients on recurrence rates and disease-free survival (DFS) was explored in breast cancer patients seen at the City of Hope from 1997 to 2012.

Methods Female breast cancer patients …


An Algorithm For Facial Expression Recognition To Assist Handicapped Individuals With Eating Disabilities, Anthony Rudolph De La Loza Jan 2011

An Algorithm For Facial Expression Recognition To Assist Handicapped Individuals With Eating Disabilities, Anthony Rudolph De La Loza

Theses Digitization Project

The purpose of this thesis is to describe an algorithm and implement a software system based upon facial expression recognition that will accurately determine the specific need of a handicapped individual pertaining to the eating process. Then based upon that need, determine the appropriate action that should be executed. This thesis aims to present a solution to allow a special needs individual to eat more efficienty and foster independence, while providing a platform for further research in the area of feature detection to assist individuals with special needs.


Computational Analyses Of The Uptake And Distribution Of Carbon Monoxide (Co) In Human Subjects, Kinnera Chada Jan 2011

Computational Analyses Of The Uptake And Distribution Of Carbon Monoxide (Co) In Human Subjects, Kinnera Chada

University of Kentucky Doctoral Dissertations

Carbon monoxide (CO) is an odorless, colorless, tasteless gas that binds to hemoglobin with high affinity. This property underlies the use of low doses of CO to determine hemoglobin mass (MHb) in the fields of clinical and sports medicine. However, hemoglobin bound to CO is unable to transport oxygen and exposure to high CO concentrations is a significant environmental and occupational health concern. These contrasting aspects of CO—clinically useful in low doses but potentially lethal in higher doses—mandates a need for a quantitative understanding of the temporal profiles of the uptake and distribution of CO …


Improving Quantitative Treatment Response Monitoring With Deformable Image Registration, Blake A. Cannon Aug 2010

Improving Quantitative Treatment Response Monitoring With Deformable Image Registration, Blake A. Cannon

Dissertations and Theses (Open Access)

Quantitative imaging with 18F-FDG PET/CT has the potential to provide an in vivo assessment of response to radiotherapy (RT). However, comparing tissue tracer uptake in longitudinal studies is often confounded by variations in patient setup and potential treatment induced gross anatomic changes. These variations make true response monitoring for the same anatomic volume a challenge, not only for tumors, but also for normal organs-at-risk (OAR). The central hypothesis of this study is that more accurate image registration will lead to improved quantitation of tissue response to RT with 18F-FDG PET/CT. Employing an in-house developed “demons” based deformable image registration algorithm, …


Cellular Automata Rules Generator For Microbial Communities, Melissa Marie Quintana Jan 2010

Cellular Automata Rules Generator For Microbial Communities, Melissa Marie Quintana

Theses Digitization Project

The purpose of this project is to provide a visual representation as program output so that the rules and the radius of effect can be estimated. Currently there is a need for a method that extracts the cellular automata rules which simulate the growth patterns of microbial communities found within extreme environments. Contains source code.


To Live And Die In Ca, Jane Frances Curnutt Jan 2010

To Live And Die In Ca, Jane Frances Curnutt

Theses Digitization Project

This thesis investigates the nature of elementary cellular automata to better understand their relationship of the models they support to the biological organisms that create the mats and soil crusts found in extreme environments here on earth. Cellular automata have been used to study growth and patterns in forests, arid desert environments, predator-prey problems, and sea shells. It has also been used to study areas of diverse epidemiology and linguistics. Cellular automata have been used as the core of computer games as well. This investigation has led to develop a graphical grammar for simple cellular automata, using L-systems, a grammar …