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Full-Text Articles in Bioinformatics

Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter May 2024

Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter

Masters Theses & Specialist Projects

Rapid docking of flexible biological macromolecules remains a significant open challenge in protein structure determination. While rigid docking is relatively simple with toolkits such as TagDock, a key obstacle to rapid flexible docking is the complexity and roughness of the free energy surface associated with protein conformational motion (often termed the many-minima problem), meaning conventional molecular dynamics methods do not effectively sample protein conformations near the interaction complex in accessible timescales. Methods such as metadynamics and replica exchange molecular dynamics exist to ameliorate this obstacle, yet these methods use nonphysical biases or random swaps to enhance sampling. In contrast, high …


Uncovering Novel Small Regulatory Rna In Protostome, Sweta Khanal May 2024

Uncovering Novel Small Regulatory Rna In Protostome, Sweta Khanal

Dissertations

Small RNAs play pivotal roles in post-transcriptional gene regulation across diverse phylum of protostomes. In this study, we investigate the functional significance of atypical miRNAs, mirtron miR-1017 in Drosophila. Through ectopic expression in neuronal cells, we demonstrate that miR-1017 extends lifespan by targeting its host transcript, acetylcholine receptor Dα2, and influencing its splicing. This novel trans-regulatory function suggests a mechanism for mirtron evolution, highlighting the interplay between splicing and post-transcriptional regulation. Additionally, we profile small RNA populations in the polychaete developmental model Capitella teleta, shedding light on the small RNA landscape in annelid worms. Our analysis reveals a rich …


Molecular Mechanisms Of Opioid Use Disorder In Human Brain Models, Emily Mendez May 2024

Molecular Mechanisms Of Opioid Use Disorder In Human Brain Models, Emily Mendez

Dissertations & Theses (Open Access)

Opioid use disorder (OUD) is a national and global public health crisis with no end in sight. While studies from animal models hint at widespread epigenetic and transcriptomic alterations of opioid drugs, the molecular consequences of long-term exposure to opioid drugs in human brain is still unclear, and human-centered translational models are necessary to discern the human cell type-specific effects of OUD.

Using postmortem brain Brodmann area 9 (BA9) from the UTHealth Brain Collection for Research on Psychiatric Disorders, I identified angiogenic gene networks perturbed in the RNA and protein of OUD subjects, as well as downregulation of many neuron-correlated …


Annotation Of Hypothetical Genes In Lactococcus Lactis Ssp. Il403, Jennifer A. Tangires Apr 2024

Annotation Of Hypothetical Genes In Lactococcus Lactis Ssp. Il403, Jennifer A. Tangires

Student Scholar Showcase

The human gastrointestinal tract (GIT) harnesses various microbial organisms involved in almost all processes of physiological homeostasis, among these are lactic acid bacteria (LAB). These bacteria, almost all of which belong to the order Lactobacillales, are able to produce lactic acid, and play an important role in food preservation because they produce bacteriocins. Bacteriocins are antimicrobial proteins that are used to fight off related bacteria in their environment that are competing for the same resources. This study focuses on a specific LAB strain, Lactococcus lactis ssp. IL1403 where 21.9% of its predicted genes have not yet been assigned a function. …


Documenting The Southern Range Terminus Of The Wood Frog (Lithobates Sylvaticus) In North America, Christian Braswell Apr 2024

Documenting The Southern Range Terminus Of The Wood Frog (Lithobates Sylvaticus) In North America, Christian Braswell

Theses

The Wood Frog (Lithobates sylvaticus) holds a remarkable position in North American amphibian biology, with its range extending from the Arctic Circle down to the near sub-tropical southeastern United States. This thesis presents a novel quantitative polymerase chain reaction analysis (qPCR) primer specific to L. sylvaticus and a survey effort regarding the southernmost distribution and detection of this species in Alabama through the application of environmental DNA (eDNA) sampling techniques. By investigating historical data and employing advanced genetic methodologies, this research provides insights into the contemporary status and distribution of the Wood Frog. This research is important to …


In Silico Analysis Of C-Type Lectins As Co-Infection Receptors Of Dengue And Chikungunya Viruses In Aedes Aegypti, Munawir Sazali, R. C. Hidayat Soesilohadi, Nastiti Wijayanti, Tri Wibawa, Arif Nur Muhammad Ansori Mar 2024

In Silico Analysis Of C-Type Lectins As Co-Infection Receptors Of Dengue And Chikungunya Viruses In Aedes Aegypti, Munawir Sazali, R. C. Hidayat Soesilohadi, Nastiti Wijayanti, Tri Wibawa, Arif Nur Muhammad Ansori

Makara Journal of Science

Aedes aegypti is a primer vector of dengue virus (DENV) and chikungunya virus (CHIKV). The susceptibility of mosquitoes to DENV and CHIKV depends on their recognition receptor of pathogens. C-type lectins (CTLs) are an important mediator of virus infection in A. aegypti. This study aims to identify potential receptors and determine the binding affinity between ligand–receptor interaction, CTLs and virus envelopes (DENV-1, 2, 3, and 4 and CHIKV) interaction based on in silico analysis. Sample sequences were obtained from GenBank (NCBI), and 10 CTLs were acquired from VectorBase. Homology modeling based on a minimum standard of 20% was processed …


Update On The Role Of Muc13 In Pancreatic Cancer: A Promising Early Detection Biomarker, Anupam Dhasmana, Swati Dhasmana, Sheema Khan, Meena Jaggi, Murali M. Yallapu, Subhash C. Chauhan Mar 2024

Update On The Role Of Muc13 In Pancreatic Cancer: A Promising Early Detection Biomarker, Anupam Dhasmana, Swati Dhasmana, Sheema Khan, Meena Jaggi, Murali M. Yallapu, Subhash C. Chauhan

Research Symposium

Background: With the rise in pancreatic cancer (PanCa) prevalence and mortality rate, by 2030 it will secure second position among leading causes of cancer-related deaths. Due to poor prognosis of PanCa only 11% of PanCa patients have a 5-year survival rate, resulting in an equal mortality rate and incidence rate. 85% of PanCa are Pancreatic ductal adenocarcinoma (PDAC). The main clinical challenge with PanCa is poor treatment outcomes due the late diagnosis. Currently, there are traditional biomarkers panels available for diagnosis, however, these biomarkers do not have optimal sensitivity and specificity for PanCa. Considering this alarming unmet clinic need, our …


Trip13’S Crucial Role In Pancreatic Cancer Progression, Swati Dhasmana, Anupam Dhasmana, Stella Rios, Iris A. Enriquez-Perez, Sheema Khan, Farrukh Afaq, Upender Manne, Murali M. Yallapu, Subhash Chauhan Mar 2024

Trip13’S Crucial Role In Pancreatic Cancer Progression, Swati Dhasmana, Anupam Dhasmana, Stella Rios, Iris A. Enriquez-Perez, Sheema Khan, Farrukh Afaq, Upender Manne, Murali M. Yallapu, Subhash Chauhan

Research Symposium

Background: Pancreatic cancer, characterized by its high mortality rate, stands as one of the most aggressive cancer forms. The projected surge in pancreatic cancer-related deaths, making it the second leading cause in the United States by 2030, underscores the urgency for effective early screening tools. This study employs data mining methods to scrutinize bioinformatic data surrounding TRIP13. Examining differential expression across various cancers, correlating TRIP13 expression with pancreatic cancer stages, exploring associations with common cancer genes, and analyzing overall survival rates constitute the core investigations. Integrated with molecular biology techniques, the study further quantifies TRIP13 expression in progressive pancreatic cancer …


Proteomic Analysis Of Stress Associated Factor Overexpression In Hepatocellular Carcinoma, Mohammad Shabir Hussain, Sophia Leslie, Amayrani Sanchez, Samantha Lopez, Kyle Doxtater, Manish Kumar Tripathi Mar 2024

Proteomic Analysis Of Stress Associated Factor Overexpression In Hepatocellular Carcinoma, Mohammad Shabir Hussain, Sophia Leslie, Amayrani Sanchez, Samantha Lopez, Kyle Doxtater, Manish Kumar Tripathi

Research Symposium

Background: Hepatocellular carcinoma (HCC) constitutes a substantial portion, accounting for 85% to 90% of liver cancers worldwide. Notably, within the Hispanic population, liver cancer mortality rates are notably higher, particularly evident in regions like the South Texas Rio Grande Valley (RGV), where nearly 90% of the populace is Latino/Hispanic. This region grapples with poverty affecting nearly 30% of its residents, coupled with elevated rates of obesity, diabetes, and low-income households, thereby fostering a prevalent environment of stress. Stress can profoundly impact cancer outcomes by compromising immune functionality and triggering inflammatory responses, potentially impairing surveillance against oncogenic triggers. The activation of …


Mmappr2: An Improved Bioinformatics Approach To Find Novel Genes, Aiden Cardall, Jonathon T. Hill, Kyle Johnsen, Connor Ward, Maliha Tasnim, Jared Taylor Mar 2024

Mmappr2: An Improved Bioinformatics Approach To Find Novel Genes, Aiden Cardall, Jonathon T. Hill, Kyle Johnsen, Connor Ward, Maliha Tasnim, Jared Taylor

Library/Life Sciences Undergraduate Poster Competition 2024

Introduction

• New genes are commonly found by randomly inducing mutations in model organisms.

• Mapping the mutations to the genome to find novel genes is difficult, time-consuming, and expensive.

• We created a bioinformatics program, MMAPPR, to automate this process.

• Here, we introduce a new algorithm, MMAPPR2, which requires little to no bioinformatics knowledge to use.

• MMAPPR2 makes several improvements that allow it to identify genes more rapidly and precisely.

• MMAPPR2 will aid the rapid identification of genes in a wide range of species and developmental systems.


Determining The Role Of Noncoding Insertion And Deletion Mutations In Lung Cancer, Zachary Everton, Matthew H. Bailey Mar 2024

Determining The Role Of Noncoding Insertion And Deletion Mutations In Lung Cancer, Zachary Everton, Matthew H. Bailey

Library/Life Sciences Undergraduate Poster Competition 2024

Background

● Cancer is a disease in which cells grow and divide at an uncontrolled rate and cause damage to surrounding tissue and is caused by mutations in the cells’ DNA.

● Though some cancer-causing mutations are inherited from parents, most cancer-causing mutations emerge over the course of a person’s life and are localized to the tumor. These localized mutations are also known as somatic mutations.

● The human genome is over 6.27 billion base pairs long and cannot be read from end to end; instead it is read in small pieces that are aligned to best-matching sequences in the …


Exploring Neuroplasticity Changes In Neurotoxin-Induced Parkinson’S Disease: A Preliminary Analysis Using Transcranial Magnetic Stimulation, Tomas Gomez Jr., Daniel Salinas, Kelsey Potter-Baker, Nawaz Hack, Ramu Vadukapuram Mar 2024

Exploring Neuroplasticity Changes In Neurotoxin-Induced Parkinson’S Disease: A Preliminary Analysis Using Transcranial Magnetic Stimulation, Tomas Gomez Jr., Daniel Salinas, Kelsey Potter-Baker, Nawaz Hack, Ramu Vadukapuram

Research Symposium

Background: Parkinson’s disease (PD) is a neurodegenerative condition that affects movement, cognition, gait, and significantly impacts one's quality of life. Studies have suggested that neurotoxin pre-exposure is related to PD pathology and progressive motor/non-motor deficits, though it remains unclear how neurotoxin exposure affects neuroplasticity. The present study aimed to examine neurotoxin–induced PD-associated neuroplasticity changes in relationship to mental acuity and PD motor functionalities.

Methods: 7 voluntary participants experiencing early-stage PD symptoms with self-reported neurotoxin pre-exposure were enrolled in the longitudinal, repeated-measures clinical study; 2 sex-matched, age-matched, and occupation-matched healthy subjects were recruited for controlled comparative analysis (n=9). UTRGV’s Institute …


Remodeling Anaplastic Thyroid Cancer's Aggressive Profile And Metabolic Signature By Natural Alkaloid Berberine, Tara Elizabeth Jarboe Mar 2024

Remodeling Anaplastic Thyroid Cancer's Aggressive Profile And Metabolic Signature By Natural Alkaloid Berberine, Tara Elizabeth Jarboe

NYMC Student Theses and Dissertations

Anaplastic thyroid cancer is a rare, fatal cancer with a five-year survival of 4%. Universally diagnosed at stage IV, anaplastic thyroid cancer is characterized by its lack of differentiation, rapid proliferative rate, highly inflammatory tumor microenvironment, and metabolic dysregulation. Refractory to all established therapies, anaplastic thyroid cancer requires a novel therapeutic approach that targets all of these drivers of anaplastic thyroid cancer carcinogenesis. We propose natural alkaloid berberine as a therapeutic with multitarget efficacy to alter mitochondrial metabolism and reprogram anaplastic thyroid cancer’s aggressive phenotype. Our in vitro model uses monocyte cell line U937, anaplastic thyroid cancer cell lines T238 …


Ursapgx: A New R Package To Annotate Pharmacogenetic Star Alleles Using Phased Whole-Genome Sequencing Data., Gennaro Calendo, Dara Kusic, Josef Madzo, Neda Gharani, Laua Scheinfeldt Mar 2024

Ursapgx: A New R Package To Annotate Pharmacogenetic Star Alleles Using Phased Whole-Genome Sequencing Data., Gennaro Calendo, Dara Kusic, Josef Madzo, Neda Gharani, Laua Scheinfeldt

Cooper Medical School of Rowan University Faculty Scholarship

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.


Integrative Genomic Insights Into Coral Resilience: Adaptive And Acclimatory Responses To Seasonal Environmental Shifts, Tasnim Ghanim Feb 2024

Integrative Genomic Insights Into Coral Resilience: Adaptive And Acclimatory Responses To Seasonal Environmental Shifts, Tasnim Ghanim

Theses and Dissertations

Coral reefs, critical to marine biodiversity and coastal protection, face escalating threats from climate change-related phenomena such as ocean warming. This warming is leading to widespread thermal stress that contributes to coral bleaching and infectious disease in corals, leading to the disruption of marine ecosystems and the economies that depend on them. Focusing on the brain coral Platygyra daedalea, known for its thermal resilience in the Persian Arabian Gulf—a region that exemplifies the extreme stressors of climate change—our study aims to dissect the genetic, transcriptomic, and microbiological underpinnings of coral survival in high-temperature environments predicted for the end of …


Investigating The Phytochemicals In Sargassum (Brown Algae) Against The Therapeutic Targets Of Oral Squamous Cell Carcinoma Metastasized From Breast: An Approach, Mahema S Feb 2024

Investigating The Phytochemicals In Sargassum (Brown Algae) Against The Therapeutic Targets Of Oral Squamous Cell Carcinoma Metastasized From Breast: An Approach, Mahema S

Annual Research Symposium

ABSTRACT:

Purpose: Oral metastases are relatively rare. In women, the most common oral metastases originate from breast cancer, the most diagnosed malignancy, and the second leading cause of death. Sargassum is a genus of brown algae which exhibits its natural therapeutic potential with anticancer properties. This study aimed to identify a therapeutic target for OSCC metastasized from breast cancer through network pharmacology and to evaluate potent phytochemicals against the identified target.

Methods: DEGs associated with OSCC and breast cancer were obtained from the Gene Expression Omnibus. The upregulated DEGs were then intersected to identify common targets between OSCC and BC. …


Interplay Of Periodontal Bacterial Metabolites In The Progression Of Coronary Artery Disease: A System Biological Approach, Janakiraman V Feb 2024

Interplay Of Periodontal Bacterial Metabolites In The Progression Of Coronary Artery Disease: A System Biological Approach, Janakiraman V

Annual Research Symposium

Purpose:

The purpose of this study is to investigate the intricate relationship between periodontal disease (PD) and coronary artery disease (CAD), as evidenced by epidemiological associations. Metalloproteinase inhibitor (TIMP1) plays a pivotal role in cellular signaling, differentiation, cell death, and migration by binding to target metalloproteinases, forming complexes with other molecules (collagenases) to inactivate them. However, the expression of TIMP1 is reduced in both PD and CAD, leading to an upregulation of other metalloproteinases. This research explores the hypothesis that metabolites released from (Porphyromonas gingivalis), a prevalent bacterium in atherosclerotic patients, may inhibit TIMP1, thereby influencing CAD progression. …


A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei Feb 2024

A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei

Computer Science Faculty Publications

The most common eye infection in people with diabetes is diabetic retinopathy (DR). It might cause blurred vision or even total blindness. Therefore, it is essential to promote early detection to prevent or alleviate the impact of DR. However, due to the possibility that symptoms may not be noticeable in the early stages of DR, it is difficult for doctors to identify them. Therefore, numerous predictive models based on machine learning (ML) and deep learning (DL) have been developed to determine all stages of DR. However, existing DR classification models cannot classify every DR stage or use a computationally heavy …


Protein-Protein Interactions In Cell Cycle Proteins: An In Silico Investigation Of Two Important Players, Andriele Eichner Feb 2024

Protein-Protein Interactions In Cell Cycle Proteins: An In Silico Investigation Of Two Important Players, Andriele Eichner

Dissertations, Theses, and Capstone Projects

The examination of the cell cycle carries significant implications for the biology, health, and overall existence of all living things. These implications span from the development and growth of these organisms to the aging process and cancer, as well as the potential of stem cell therapies to repair diseases and injuries. Numerous proteins of the cell cycle are essential for cellular division and proliferation and are widely conserved over the course of evolution. In this work, we aimed to investigate the molecular processes of protein-protein interactions in cell cycle proteins, centering on two key players: Cdc6 in budding yeast and …


Toward Improved Global Food Security: Uncovering How Tomatoes Fight Root-Knot Nematodes, Chingyan H. Huang Jan 2024

Toward Improved Global Food Security: Uncovering How Tomatoes Fight Root-Knot Nematodes, Chingyan H. Huang

The Journal of Purdue Undergraduate Research

No abstract provided.


Exploring The Evolution Of Callose Synthase In Green Plants, Giovanna Durante Jan 2024

Exploring The Evolution Of Callose Synthase In Green Plants, Giovanna Durante

The Journal of Purdue Undergraduate Research

No abstract provided.


Elastin-Like Polypeptide As A Model To Study Intrinsically Disordered Proteins, Sadegh Majdi Jan 2024

Elastin-Like Polypeptide As A Model To Study Intrinsically Disordered Proteins, Sadegh Majdi

Theses and Dissertations

The elastin-like polypeptide (ELP) is a well-studied structural protein that is easily amenable to amino acid (AA) sequence modifications and has the potential to yield a wide variety of uses in bioengineering and biomedical applications. One unique property of ELP is the inclusion of intrinsically disordered domains (IDP) within the structure that allow for its diversity of physical properties. While it is generally understood that amino acid sequence dictates protein folding arrangements, the contributions of specific amino acid sequences to the intrinsic disorder of ELP has yet to be fully resolved. Therefore, identifying the contributions of specific amino acid sequences …


Integrated Rules Classifier For Predicting Pathogenic Non-Synonymous Single Nucleotide Variants In Human, Ahmed Barakat Hosseny, Marwa Said Hassan, A A. Shalan, Shymaa Khamis, M I. Dessouky Jan 2024

Integrated Rules Classifier For Predicting Pathogenic Non-Synonymous Single Nucleotide Variants In Human, Ahmed Barakat Hosseny, Marwa Said Hassan, A A. Shalan, Shymaa Khamis, M I. Dessouky

Basic Science Engineering

The most prevalent kind of genetic variants in humans are non-synonymous single nucleotide variants (nsSNVs). Several prediction tools have been launched to forecast the effect of amino acid substitutes on human protein function. These tools sort variants as pathogenic or neutral. We developed an Integrated Rules Classifier (Integration Score through JRip “ISTJRip”), which integrates the four individual tools that are publicly available; iFish, Mutation Assessor, FATHMM, and SIFT-based on the JRip machine learning technique. Additionally, we compared the ISTJRip approach with the other three created integration classifiers; Integration Score through J48 “ISTJ48”, Integration Score through RF “ISTRF”, and Integration …


A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu Jan 2024

A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of biotechnology and information technology has brought life sciences into a new era of data explosion. The traditional life science research paradigm struggles to reveal the fundamental rules of complex biological systems from rapidly growing biological big data. As artificial intelligence continues to achieve disruptive breakthroughs in life science, a new paradigm driven by AI is emerging. This study delves into typical examples of life science research driven by AI, proposes the concept and key elements of the new life science research paradigm, elaborates on the cutting-edge of life science research under this new paradigm, and discusses …


Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas Jan 2024

Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas

Theses and Dissertations--Chemical and Materials Engineering

Hydrophobic deep eutectic solvents (DESs) have emerged as excellent extractants. A major challenge is the lack of an efficient tool to discover DES candidates. Currently, the search relies heavily on the researchers’ intuition or a trial-and-error process, which leads to a low success rate or bypassing of promising candidates. DES performance depends on the heterogeneous hydrogen bond environment formed by multiple hydrogen bond donors and acceptors. Understanding this heterogeneous hydrogen bond environment can help develop principles for designing high performance DESs for extraction and other separation applications. This work investigates the structure and dynamics of hydrogen bonds in hydrophobic DESs …


When Brain Meets Artificial Intelligence, Lu Zhang Jan 2024

When Brain Meets Artificial Intelligence, Lu Zhang

Computer Science and Engineering Dissertations

When we review the history of development of artificial intelligence (AI), we will find that brain science plays a pivotal role in fostering breakthroughs in AI, such as artificial neural networks (ANNs). Today, AI has made remarkable strides, particularly with the emergence of large language models (LLMs), surpassing expectations and achieving human-level performance in certain tasks. Nonetheless, an insurmountable gap remains between AI and human intelligence. It is urgent to establish a bridge between brain science and AI, promoting their mutual enhancement and collaborations. This involve establishing connections from brain science to AI (brain-inspired AI), and reversely, from AI to …


Environmental Biology Masters Capstone, Antonio Gonzalez-Pita Jan 2024

Environmental Biology Masters Capstone, Antonio Gonzalez-Pita

Regis University Student Publications (comprehensive collection)

Human wildlife interactions (HWI) pose a complex challenge for wildlife managers. Human encroachment into wildlife habitat and the growing number of outdoor recreationists are increasing the frequency of contact and conflict, especially in regions such as the Front Range of Colorado. Geographic information systems (GIS), which use a combination of remote sensing and environmental survey data, allow for predictive spatial analyses of where human wildlife interactions are likely to occur. I used publicly reported observations of moose to create spatial predictive maps in a species distribution model framework. Slope and elevation were shown to be the strongest predictors of HWI, …


Using Single Cell Genomics To Explore The Impact Of Marine Viruses On Microbial Respiration., Paxton Tomko Jan 2024

Using Single Cell Genomics To Explore The Impact Of Marine Viruses On Microbial Respiration., Paxton Tomko

MCB Articles

Viral metabolic reprograming of marine prokaryotes, through the use of virally encoded auxiliary metabolic genes (AMGs), plays a critical role in marine ecosystem function by influencing biochemical cycles and genetic diversity in these environments. Despite the fundamental role viruses play in global environmental ecosystems, they remain an understudied aspect of microbial ecology and evolution, in part due to the methods available for studying virus host interactions in natural systems. Thus far, metagenomic analyses have been used to study the interactions of virus host pairs, but these types of analyses have their limitations in accurately linking viruses to hosts, or culture-based …


Whole Genome Sequencing For The Millipede Cherokia Georgiana, Elena Cruz, Will Wittstock, Daniel Hastings, Arnab Sengupta, Bruce A. Snyder Jan 2024

Whole Genome Sequencing For The Millipede Cherokia Georgiana, Elena Cruz, Will Wittstock, Daniel Hastings, Arnab Sengupta, Bruce A. Snyder

Graduate Research Showcase

Out of thousands of known millipede species, only five sequenced genomes of species (in four of sixteen orders) are publicly available. No whole genomes and limited genetic information are available for incredibly diverse families such as Xystodesmidae. Our research goal is to sequence the whole genome of the millipede Cherokia georgiana. A de novo sequence of the complete genome of a North American species will facilitate future research in understanding gene expression under a variety of conditions. Many interesting biological processes in millipedes are poorly described, such as the production of a defensive hydrogen cyanide secretion found in the …


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 Jan 2024

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 …