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Articles 1 - 30 of 279
Full-Text Articles in Medical Biomathematics and Biometrics
Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman
Undergraduate Research Posters
Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
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 …
Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison Of Brain- Cousens And Cedergreen Models For A Biochemical Dataset, Venkat D. Abbaraju, Tamaraty L. Robinson, Brian P. Weiser
Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison Of Brain- Cousens And Cedergreen Models For A Biochemical Dataset, Venkat D. Abbaraju, Tamaraty L. Robinson, Brian P. Weiser
Rowan-Virtua School of Osteopathic Medicine Faculty Scholarship
Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for “hormetic” dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change …
Relative Burden Of Cancer And Noncancer Mortality Among Long-Term Survivors Of Breast, Prostate, And Colorectal Cancer In The Us, Madhav Kc, Jane Fan, Terry Hyslop, Sirad Hassan, Michael Cecchini, Shi-Yi Wang, Andrea Silber, Michael S. Leapman, Ira Leeds, Stephanie B. Wheeler, Lisa P. Spees, Cary P. Gross, Maryam Lustberg, Rachel A. Greenup, Amy C. Justice, Kevin C. Oeffinger, Michaela A. Dinan
Relative Burden Of Cancer And Noncancer Mortality Among Long-Term Survivors Of Breast, Prostate, And Colorectal Cancer In The Us, Madhav Kc, Jane Fan, Terry Hyslop, Sirad Hassan, Michael Cecchini, Shi-Yi Wang, Andrea Silber, Michael S. Leapman, Ira Leeds, Stephanie B. Wheeler, Lisa P. Spees, Cary P. Gross, Maryam Lustberg, Rachel A. Greenup, Amy C. Justice, Kevin C. Oeffinger, Michaela A. Dinan
Kimmel Cancer Center Faculty Papers
IMPORTANCE: Improvements in cancer outcomes have led to a need to better understand long-term oncologic and nononcologic outcomes and quantify cancer-specific vs noncancer-specific mortality risks among long-term survivors.
OBJECTIVE: To assess absolute and relative cancer-specific vs noncancer-specific mortality rates among long-term survivors of cancer, as well as associated risk factors.
DESIGN, SETTING, AND PARTICIPANTS: This cohort study included 627 702 patients in the Surveillance, Epidemiology, and End Results cancer registry with breast, prostate, or colorectal cancer who received a diagnosis between January 1, 2003, and December 31, 2014, who received definitive treatment for localized disease and who were alive 5 …
Modeling The Immune Response To Immunotherapy And Triple Negative Breast Cancer In Mice, Dayton J. Syme, Angelica Davenport, Yun Lu, Anna G. Sorace, Nicholas G. Cogan
Modeling The Immune Response To Immunotherapy And Triple Negative Breast Cancer In Mice, Dayton J. Syme, Angelica Davenport, Yun Lu, Anna G. Sorace, Nicholas G. Cogan
Biology and Medicine Through Mathematics Conference
No abstract provided.
Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile
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 …
Development Of A Novel Mathematical Model That Explains Sars-Cov-2 Infection Dynamics In Caco-2 Cells, Vladimir Staroverov, Stepan Nersisyan, Alexei Galatenko, Dmitriy Alekseev, Sofya Lukashevich, Fedor Ployakov, Nikita Anisimov, Alexander Tonevitsky
Development Of A Novel Mathematical Model That Explains Sars-Cov-2 Infection Dynamics In Caco-2 Cells, Vladimir Staroverov, Stepan Nersisyan, Alexei Galatenko, Dmitriy Alekseev, Sofya Lukashevich, Fedor Ployakov, Nikita Anisimov, Alexander Tonevitsky
COVID-19 Papers, Posters, and Presentations
Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for in vitro data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed …
Adaptive Critic Network For Person Tracking Using 3d Skeleton Data, Joseph G. Zalameda, Alex Glandon, Khan M. Iftekharuddin, Mohammad S. Alam (Ed.), Vijayan K. Asari (Ed.)
Adaptive Critic Network For Person Tracking Using 3d Skeleton Data, Joseph G. Zalameda, Alex Glandon, Khan M. Iftekharuddin, Mohammad S. Alam (Ed.), Vijayan K. Asari (Ed.)
Electrical & Computer Engineering Faculty Publications
Analysis of human gait using 3-dimensional co-occurrence skeleton joints extracted from Lidar sensor data has been shown a viable method for predicting person identity. The co-occurrence based networks rely on the spatial changes between frames of each joint in the skeleton data sequence. Normally, this data is obtained using a Lidar skeleton extraction method to estimate these co-occurrence features from raw Lidar frames, which can be prone to incorrect joint estimations when part of the body is occluded. These datasets can also be time consuming and expensive to collect and typically offer a small number of samples for training and …
Population Variations Of Cheiloscopy Patterns: A Cross-Sectional Observation Pilot Study, Emily Smith Regan, Brenda T. Bradshaw, Ann M. Bruhn, Walter Melvin, Sinjini Sikdar
Population Variations Of Cheiloscopy Patterns: A Cross-Sectional Observation Pilot Study, Emily Smith Regan, Brenda T. Bradshaw, Ann M. Bruhn, Walter Melvin, Sinjini Sikdar
Dental Hygiene Faculty Publications
Purpose Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.
Methods This IRB approved blinded cross-sectional observation pilot study collected lip prints from sixty-six individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for …
Computer-Aided Drug Discovery For Helicobacter Pylori, Nicole Ann Vita
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 …
A Two-Layer Continuous-Capillary Oxygen Transport Model: Development And Application To Blood Flow Regulation In Resting Skeletal Muscle., Keith C. Afas
Electronic Thesis and Dissertation Repository
In skeletal muscle (SM), the microcirculation distributes blood flow to capillary networks to meet local oxygen (O2) demand. Experiments using intra-vital video microscopy (IVVM) have quantified blood flow and O2 supply in capillary networks, and using an O2 exchange chamber have measured local changes in blood flow believed due to O2-dependent regulation. However, IVVM is unable to simultaneously measure capillary O2 supply and SM O2 content, implying the need for theoretical models to understand how flow regulation and SM oxygenation interact. In this thesis, a novel blood-tissue O2 transport model using …
A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang
A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang
Faculty Publications
Immunotherapy is an innovative treatment that enlists the patient's immune system to battle tumors. The optimal dose for treating patients with an immunotherapeutic agent may differ according to their biomarker status. In this article, we propose a biomarker-based phase I/II dose-finding design for identifying subgroup-specific optimal dose for immunotherapy (BSOI) that jointly models the immune response, toxicity, and efficacy outcomes. We propose parsimonious yet flexible models to borrow information across different types of outcomes and subgroups. We quantify the desirability of the dose using a utility function and adopt a two-stage dose-finding algorithm to find the optimal dose for each …
Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte
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 …
Demographics Of Periprosthetic Joint Infection Rates, Katelynn Donnelly, Abigail Erwin, Andrew Chapple, Peter Krause, Vinod Dasa
Demographics Of Periprosthetic Joint Infection Rates, Katelynn Donnelly, Abigail Erwin, Andrew Chapple, Peter Krause, Vinod Dasa
Medical Research Day
Introduction: Risk factors for periprosthetic joint infections (PJIs) following total joint arthroplasties (TJAs) include patient demographics and comorbidities such as age, gender, obesity, rheumatoid arthritis, and diabetes. 1 However, there is insufficient research analyzing the number of PJIs in certain racial subsets of the population despite the presence of disparities due to race that still exists in orthopedics today. 2 The purpose of this study is to investigate if PJI rates differ by race, as well as other patient demographics. This may uncover valuable information on how race relates to PJIs which is frequently unaccounted for in other studies. This …
Lack Of Demographic Information In Tha/Tka Randomized Controlled Trial Publications, Katelynn Donnelly, Hannah Theriot, John Bourgeois, Andrew Chapple, Peter Krause, Vinod Dasa
Lack Of Demographic Information In Tha/Tka Randomized Controlled Trial Publications, Katelynn Donnelly, Hannah Theriot, John Bourgeois, Andrew Chapple, Peter Krause, Vinod Dasa
Medical Research Day
Introduction: The impact of social determinants of health (SDOH) has been documented in orthopedic literature. However, there is a lack of data on the inclusion of these variables in orthopedic studies. Our aim was to investigate how many THA and TKA randomized controlled trials (RCTs) report SDOH variables such as race, ethnicity, insurance, income, and education within the manuscript. Methods: A literature review was conducted on a PubMed search for RCTs published from 2017-2019 in 4 major orthopedic journals which routinely publish on total joint arthroplasty: JBJS, Journal of Arthroplasty, CORR, and Osteoarthritis and Cartilage. The inclusion criteria, THA/TKA RCTs …
Demographics Of Periprosthetic Joint Infections Rates, Katelynn Donnelly, Abigail Erwin, Andrew Chapple, Peter Krause, Vinod Dasa
Demographics Of Periprosthetic Joint Infections Rates, Katelynn Donnelly, Abigail Erwin, Andrew Chapple, Peter Krause, Vinod Dasa
Medical Research Day
Introduction: Risk factors for periprosthetic joint infections (PJIs) following total joint arthroplasties (TJAs) include patient demographics and comorbidities such as age, gender, obesity, rheumatoid arthritis, and diabetes. However, there is insufficient research analyzing the number of PJIs in certain racial subsets of the population despite the presence of disparities due to race that still exists in orthopedics today. The purpose of this study is to investigate if PJI rates differ by race, as well as other patient demographics. This may uncover valuable information on how race relates to PJIs which is frequently unaccounted for in other studies. This study aims …
Neutrophil Dynamics Affect Mycobacterium Tuberculosis Granuloma Outcomes And Dissemination, Caitlin Hult, Joshua T. Mattila, Hannah P. Gideon, Jennifer J. Linderman, Denise E. Kischner
Neutrophil Dynamics Affect Mycobacterium Tuberculosis Granuloma Outcomes And Dissemination, Caitlin Hult, Joshua T. Mattila, Hannah P. Gideon, Jennifer J. Linderman, Denise E. Kischner
Math Faculty Publications
Neutrophil infiltration into tuberculous granulomas is often associated with higher bacteria loads and severe disease but the basis for this relationship is not well understood. To better elucidate the connection between neutrophils and pathology in primate systems, we paired data from experimental studies with our next generation computational model GranSim to identify neutrophil-related factors, including neutrophil recruitment, lifespan, and intracellular bacteria numbers, that drive granuloma-level outcomes. We predict mechanisms underlying spatial organization of neutrophils within granulomas and identify how neutrophils contribute to granuloma dissemination. We also performed virtual deletion and depletion of neutrophils within granulomas and found that neutrophils play …
Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly
Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly
Publications and Research
One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …
The Effect Of Using Bolometric Exercises On Enhancing Explosive Strength Among Female Students Of The Faculty Of Physical Education At Yarmouk University, Mohammed A. Mqableh, Sulaiman M. Qazaqzeh, Bassam M. Khalifa, Sumayeh M. Ekhwelah
The Effect Of Using Bolometric Exercises On Enhancing Explosive Strength Among Female Students Of The Faculty Of Physical Education At Yarmouk University, Mohammed A. Mqableh, Sulaiman M. Qazaqzeh, Bassam M. Khalifa, Sumayeh M. Ekhwelah
Journal of the Association of Arab Universities for Research in Higher Education (مجلة اتحاد الجامعات العربية (للبحوث في التعليم العالي
The Effect of Using bolometric Exercises on Enhancing Explosive Strength among Female Students of the Faculty of Physical Education at Yarmouk University. The study purpose was to identify the effect of bolometric exercises on improving the explosive force of female students in the Faculty of Physical Education at Yarmouk University. The researchers used the experimental method. The sample consisted of 22 students in the course of preparation and physical fitness for the first semester of the academic year (2018-2019) and the sample was chosen by randomly. The researchers designed a training program that includes training exercises, consisting of (18) training …
Covid19 Disease Map, A Computational Knowledge Repository Of Virus–Host Interaction Mechanisms, Marek Ostaszewski, Tomáš Helikar, Bhanwar Lal Puniya, A Host Of Co-Authors, Covid-19 Disease Map Community
Covid19 Disease Map, A Computational Knowledge Repository Of Virus–Host Interaction Mechanisms, Marek Ostaszewski, Tomáš Helikar, Bhanwar Lal Puniya, A Host Of Co-Authors, Covid-19 Disease Map Community
Department of Biochemistry: Faculty Publications
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, …
Testing The Effect Of Acetaminophen Overdose On The Liver And The Role Of Biomarkers To Predict Death Or Survival, Christine Brasic
Testing The Effect Of Acetaminophen Overdose On The Liver And The Role Of Biomarkers To Predict Death Or Survival, Christine Brasic
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Differential Geometry-Based Machine Learning Algorithm For The Brain Age Problem, Justin Asher, Khoa Tan Dang, Maxwell Masters
A Differential Geometry-Based Machine Learning Algorithm For The Brain Age Problem, Justin Asher, Khoa Tan Dang, Maxwell Masters
The Journal of Purdue Undergraduate Research
No abstract provided.
Automatic Recognition, Segmentation, And Sex Assignment Of Nocturnal Asthmatic Coughs And Cough Epochs In Smartphone Audio Recordings: Observational Field Study, Filipe Barata, Peter Tinschert, Frank Rassouli, Claudia Steurer-Stey, Elgar Fleisch, Milo Puhan, Martin Brutsche, David Kotz, Tobias Kowatsch
Automatic Recognition, Segmentation, And Sex Assignment Of Nocturnal Asthmatic Coughs And Cough Epochs In Smartphone Audio Recordings: Observational Field Study, Filipe Barata, Peter Tinschert, Frank Rassouli, Claudia Steurer-Stey, Elgar Fleisch, Milo Puhan, Martin Brutsche, David Kotz, Tobias Kowatsch
Dartmouth Scholarship
Background: Asthma is one of the most prevalent chronic respiratory diseases. Despite increased investment in treatment, little progress has been made in the early recognition and treatment of asthma exacerbations over the last decade. Nocturnal cough monitoring may provide an opportunity to identify patients at risk for imminent exacerbations. Recently developed approaches enable smartphone-based cough monitoring. These approaches, however, have not undergone longitudinal overnight testing nor have they been specifically evaluated in the context of asthma. Also, the problem of distinguishing partner coughs from patient coughs when two or more people are sleeping in the same room using contact-free audio …
Impact Of Order Set Use On Stroke Care, Bilal Nadeem, Edward Waseleski, Meryem Maras-Casey, Sabih Alam, Adnan Faruqui, Michael Gutierrez, Maruthsakhi Molugu, Christina Oricompil, Ashar Mahmood, Katherine Torralba, Fatima Agha, Nour Tlimat, Olu Oyesanmi, Irina Davis, Salman Muddassir, Nikolay Mitzov
Impact Of Order Set Use On Stroke Care, Bilal Nadeem, Edward Waseleski, Meryem Maras-Casey, Sabih Alam, Adnan Faruqui, Michael Gutierrez, Maruthsakhi Molugu, Christina Oricompil, Ashar Mahmood, Katherine Torralba, Fatima Agha, Nour Tlimat, Olu Oyesanmi, Irina Davis, Salman Muddassir, Nikolay Mitzov
West Florida Division Virtual Research Day 2020
- A case control study on stroke patients was recently completed for a quality improvement (QI) investigation.
- The objective was to determine if the use of either Hemorrhagic or Ischemic Stroke Order Set had an effect on the length of stay (LOS) or adherence to current stroke guideline recommendations
A Mathematical Model To Explore The Potential Of Combinations Of Adt And Immunotherapies, Johnna Barnaby
A Mathematical Model To Explore The Potential Of Combinations Of Adt And Immunotherapies, Johnna Barnaby
Biology and Medicine Through Mathematics Conference
No abstract provided.
452— Potential Impacts Of Basic Reproduction Number On The Covid-19 Epidemic, Marisa Presutto
452— Potential Impacts Of Basic Reproduction Number On The Covid-19 Epidemic, Marisa Presutto
GREAT Day Posters
The basic reproduction number (R0) of a disease can be thought of as the number of cases that one case will directly generate if the rest of the population is susceptible to infection. The R0 of COVID-19 has recently become clearer; toward the beginning of the outbreak, the Imperial College Group estimated it to be somewhere between 1.5 and 3.5 (Imai et al. 2020), but they have now assumed a value of 2.4 (Ferguson et al. 2020). Using the Watts-Strogatz small-world model, I examined the effects of different R0 values within the original range on the …
Mathematical Model Of Atm Activation And Chromatin Relaxation By Ionizing Radiation, Yongfeng Li, Francis A. Cucinotta
Mathematical Model Of Atm Activation And Chromatin Relaxation By Ionizing Radiation, Yongfeng Li, Francis A. Cucinotta
Healthcare Administration & Policy Faculty Publications
International Journal of Molecular Sciences
Quantifying The Heterogeneity Of The Immunoglobulin G N-Glycome In An Ageing Australian Population: The Busselton Healthy Ageing Study, Alyce Russell
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, …
Connectivity Differences Between Gulf War Illness (Gwi) Phenotypes During A Test Of Attention, Tomas Clarke, Jessie Jamieson, Patrick Malone, Rakib U. Rayhan, Stuart Washington, John W. Vanmeter, James N. Baraniuk
Connectivity Differences Between Gulf War Illness (Gwi) Phenotypes During A Test Of Attention, Tomas Clarke, Jessie Jamieson, Patrick Malone, Rakib U. Rayhan, Stuart Washington, John W. Vanmeter, James N. Baraniuk
Department of Mathematics: Faculty Publications
One quarter of veterans returning from the 1990–1991 Persian Gulf War have developed Gulf War Illness (GWI) with chronic pain, fatigue, cognitive and gastrointestinal dysfunction. Exertion leads to characteristic, delayed onset exacerbations that are not relieved by sleep. We have modeled exertional exhaustion by comparing magnetic resonance images from before and after submaximal exercise. One third of the 27 GWI participants had brain stem atrophy and developed postural tachycardia after exercise (START: Stress Test Activated Reversible Tachycardia). The remainder activated basal ganglia and anterior insulae during a cognitive task (STOPP: Stress Test Originated Phantom Perception). Here, the role of attention …
Deepcon-Pre: Improved Protein Contact Map Prediction Using Inverse Covariance And Deep Residual Networks, Nachammai Palaniappan
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 …