Life Sciences Commons^™

Structure-Based Discovery Of Malate Dehydrogenase Inhibitors With Efficacy Against C. Parvum Oocysts, Ankita Bharatbhai Kheni

Biochemistry and Molecular Biology

Cryptosporidium parvum, the etiological agent of Cryptosporidiosis (diarrheal illness) represents a significant global health burden, particularly affecting immunodeficient and pediatric populations. Since the parasite has a highly reduced mitochondrion and relies on glycolysis, enzymes such as C. parvum malate dehydrogenase (CpMDH), which are believed to be indispensable for parasite viability due to their pivotal roles in NAD⁺ regeneration and redox balance, remain largely unexplored as therapeutic targets. The present study employed a multifaceted experimental and computational strategy to evaluate the inhibitory activity of two lead-like and drug-like small molecules, referred to as compound 1.8 and compound 1.5, against the cofactor …

Discovery Of Bmi-Associated Gut Microbiome Signatures In The Awi-Gen 2 Cohort, Meriem Yagoubi

Theses and Dissertations

Obesity is increasing across sub-Saharan Africa amid rapid dietary, environmental, and urbanization transitions, yet the gut microbiome features associated with adiposity in African populations remain under-characterized. This study investigated whether species-level gut microbiome composition is associated with body mass index (BMI) in the AWI-Gen 2 cohort, and whether BMI-associated microbial signals remain detectable after accounting for the dominant geographic structure of the microbiome. Gut microbiome community structure and diversity were characterized across 1,665 participants, and differential abundance analysis was used to identify taxa associated with BMI after controlling for study site. Machine learning models were then trained to assess how …

Biologically Informed Negative Samplingfor Antibody Chain Pairing Classification, Ishita Singh

Computer Science Senior Theses

Antibody heavy and light chain (H/L) pairing is fundamental to antigen recognition and stability. While single-cell sequencing preserves native pairing information, widely used bulk repertoire and spatial transcriptomics platforms do not, motivating the need for efficient ML methods to infer H/L pairing. Training a binary classifier for this task faces the methodological challenge of a lack of true biological negatives, since natural selection eliminates B cells with incompatible H/L pairs.

In this thesis, I introduce a biologically informed negative sampling strategy for H/L pairing classification, drawing on known V-gene biases in heavy and light chain pairing. Pseudo-negatives are constructed by …

Nmda Receptor Subunit Nmr-2 Regulates Pathogen-Induced Immune Responses Via The Nervous System In C. Elegans, Benson Otarigho, Jonathan Lalsiamthara, Alejandro Aballay

Faculty, Staff and Student Publications

Neural control of innate immunity must balance restraint of basal immune activity with rapid activation upon pathogen encounter. Glutamate, the primary excitatory neurotransmitter in the nervous system, has been implicated in several neurological disorders associated with inflammation, suggesting a potential link to immune regulation. However, how glutamatergic signaling contributes to immune balance remains unknown. Here, we demonstrated that the NMDA-type ionotropic glutamate receptor subunit NMR-2, a component of the NMDA receptor complex, acts in the

Large Scale Kmer-Based Proteomic Analysis: An Application Towards Evolutionary Constraint Discovery, Matthew Chak

Master's Theses

Large protein databases now make it possible to study short peptides across natural protein sequence space at unprecedented scale, but exhaustively counting k-mers across billions of protein sequences remains computationally difficult. This thesis develops an exact amino-acid k-mer counting method based on direct addressing, in which fixed-length amino-acid strings are encoded as base-20 integers and updated with a sliding-window recurrence. By avoiding key storage and collision resolution, this approach removes overhead inherent to hash-map-based methods when the k-mer space is sufficiently dense. A memory analysis shows when direct addressing is preferable to open-addressing hash tables, and expected-saturation calculations motivate its …

Ldm-Morph: Latent Diffusion Model Guided Deformable Image Registration, Jiong Wu, Tinsu Pan, Kuang Gong

Faculty, Staff and Student Publications

Deformable image registration plays an essential role in various medical image tasks. Existing deep learning-based deformable registration frameworks primarily utilize convolutional neural networks (CNNs) or Transformers to learn features to predict the deformations. However, the lack of semantic information in the learned features limits the registration performance. Furthermore, the similarity metric of the loss function is often evaluated only in the pixel space, which ignores the matching of high-level anatomical features and can lead to deformation folding. To address these issues, in this work, we proposed LDM-Morph, an unsupervised deformable registration algorithm for medical image registration. LDM-Morph integrated features extracted …

Exploring Csf Microrna Signatures As Diagnostic Biomarkers In Adult-Type Diffuse Gliomas, Maryam Pirhoushiaran, Kamilah Walker-Charles, Tsung-Hung Yao, Satwikreddy Putluri, Nehal Patel, Daniel H Wang, Isabel Wang, Srividya Arjuna, Antonio Dono, Angel Bueno, Sophia Nguyen, Ashish P Balar, Jason T Huse, Suprateek Kundu, Yoshua Esquenazi, Chirag B Patel, Sujit S Prabhu, Frederick F Lang, Leomar Y Ballester

Faculty, Staff and Student Publications

Mutations in isocitrate dehydrogenase (IDH) genes, specifically IDH1 and IDH2, are frequently observed in diffuse gliomas (DG) and define distinct molecular subtypes, namely IDH-wildtype and IDH-mutant. Abnormal expression of extracellular vesicle-derived microRNAs (EV-miRNAs) in the cerebrospinal fluid (CSF) of DG patients may serve as minimally invasive diagnostic and prognostic biomarkers. To investigate this potential, we employed miRNA-sequencing (miRNA-seq), quantitative real-time PCR (qRT-PCR), and multivariable logistic regression (MLR) to identify differentially expressed microRNAs (DE-miRNAs) in CSF samples from DG patients. qRT-PCR analysis demonstrated that EV-miR-21-5p effectively differentiated CSF from glioblastoma (GBM) patients versus controls (p = 0.012, AUC = 0.84) and …

Exploring Csf Microrna Signatures As Diagnostic Biomarkers In Adult-Type Diffuse Gliomas, Maryam Pirhoushiaran, Kamilah Walker-Charles, Tsung-Hung Yao, Satwikreddy Putluri, Nehal Patel, Daniel H Wang, Isabel Wang, Srividya Arjuna, Antonio Dono, Angel Bueno, Sophia Nguyen, Ashish P Balar, Jason T Huse, Suprateek Kundu, Yoshua Esquenazi, Chirag B Patel, Sujit S Prabhu, Frederick F Lang, Leomar Y Ballester

Faculty, Staff and Student Publications

Mutations in isocitrate dehydrogenase (IDH) genes, specifically IDH1 and IDH2, are frequently observed in diffuse gliomas (DG) and define distinct molecular subtypes, namely IDH-wildtype and IDH-mutant. Abnormal expression of extracellular vesicle-derived microRNAs (EV-miRNAs) in the cerebrospinal fluid (CSF) of DG patients may serve as minimally invasive diagnostic and prognostic biomarkers. To investigate this potential, we employed miRNA-sequencing (miRNA-seq), quantitative real-time PCR (qRT-PCR), and multivariable logistic regression (MLR) to identify differentially expressed microRNAs (DE-miRNAs) in CSF samples from DG patients. qRT-PCR analysis demonstrated that EV-miR-21-5p effectively differentiated CSF from glioblastoma (GBM) patients versus controls (p = 0.012, AUC = 0.84) and …

Nlrp3 Inflammasome: A Link Between Systemic Infection And Alzheimer’S Disease, Tatiana Barichello, Felipe Dal-Pizzol

Faculty, Staff and Student Publications

No abstract provided.

Investigating Cryptic Diversity In The Hawaiian Endemic Plant, Psychotria Mariniana (Rubiaceae), Uyen Thi Hoang Nguyen

Master's Theses

Islands, with their isolation and steep environmental gradients, serve as natural laboratories for studying speciation. Molecular phylogenetic and population genetic methods utilizing Next-Generation Sequencing (NGS) have revolutionized our ability to document patterns of genetic divergence and diversity. Cryptic diversity, genetically distinct populations that were previously unrecognized as unique, and cryptic speciation, where divergent genetic populations may be deserving of status as unique species, have been observed in many taxa. The Hawaiian Islands provide an ideal setting for studying divergence and speciation due to their extreme isolation, known ages, and volcanic origin. Previous work has investigated the evolutionary relationships of the …

In Silico Molecular Docking Study Of Antidiabetic Bioactive Compounds From Brotowali (Tinospora Cordifolia) Targeting Glut4 In Type Ii Diabetes Mellitus, Gita Euaggelion Tarigan, Surya Dwira

Indonesian Journal of Medical Chemistry and Bioinformatics

Type 2 diabetes mellitus (T2DM) is a global metabolic disorder characterized by insulin resistance and impaired glucose uptake. Despite the availability of pharmacological therapies, limitations such as adverse effects and high costs highlight the need for alternative therapeutic candidates. Tinospora cordifolia has been widely reported to contain bioactive compounds with antidiabetic potential; however, comparative evaluation of their interaction with glucose transporter type 4 (GLUT4) remains limited.

This study aimed to identify the most promising bioactive compounds from Tinospora cordifolia targeting GLUT4 using an in silico molecular docking approach, followed by pharmacokinetic and toxicity (ADMET) prediction. Molecular docking was performed using …

Genomics And Bioinformatics Student Companion Workbook (First Edition), Na Xu, Tina Hu

Open Educational Resources

This Genomics and Bioinformatics Student Companion Workbook provides an integrated, hands-on introduction to the principles and applications of modern genomics and bioinformatics. Designed for undergraduate students, the workbook guides learners from foundational concepts of genome structure and sequencing technologies to advanced topics including variant analysis, comparative genomics, and multi-omics integration. Emphasizing the interplay between experimental biology and computational analysis, it introduces key analytical tools and biological databases that support genome interpretation and data-driven discovery.

Through a structured progression of chapters, students explore genome organization across diverse biological systems, from prokaryotes and viruses to complex eukaryotic genomes, and examine how genomic …

Accuracy Of Parameter Estimation For A Simple Gene Regulatory Network Model Is Sensitive To Network Motif, Number Of Parameters Estimated, And Magnitude And Direction Of Regulatory Relationships, Nikki C. Chun, Kam Dahlquist

Honors Thesis

A gene regulatory network (GRN) is a set of transcription factors that regulate the expression of genes encoding other transcription factors. The dynamics of a GRN explain how gene expression changes over time. GRNmap is a MATLAB software package that uses ordinary differential equations to model dynamics of small-scale GRNs. We used the program to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in three related literature-derived GRNs based on yeast cold shock microarray data previously collected in the Dahlquist Lab. We noticed large differences in estimated weight values when 1-2% of the expression values were …

Phase-Preserving Machine Learning Forecasting Of Nonlinear Predator–Prey Dynamics, Saira Batool, Muhammad Imran, Brett Mckinney

Biology and Medicine Through Mathematics Conference

No abstract provided.

Unc-45b As A Potential Chaperone For The Transcription Factor, Gata-4, Kaylah Owings

Electronic Theses and Dissertations

The cardiac myosin–specific chaperone UNC-45B has been shown to physically interact with the cardiac myosin transcription factor GATA-4. Specifically, this interaction occurs within the chaperoning region of UNC-45B, known as the UCS domain. However, the precise nature of this interaction has not yet been fully elucidated. The present study was conducted to confirm earlier findings and to evaluate whether UNC-45B functions as a chaperone for GATA-4 using bioinformatic approaches. Analysis of the interaction using AlphaFold 3 modeling verified not only that binding occurs at the UCS (chaperoning) domain of UNC-45B, but also that the interaction is associated with an increase …

Bioinformatic Resolution Of Candidate Stress-Response Homologs In Cryptosporidium Parvum: P53-Family Vs Sestrin Identity, Freeman Tobechukwu Ezeala Mr.

Biochemistry and Molecular Biology

Cryptosporidium parvum is an apicomplexan protozoan of major public-health importance, but accurate genome annotation in this organism remains difficult because of its compact genome, deep protein divergence, and the presence of compositionally biased or low-complexity regions that can mislead similarity-based analysis.

In this thesis, I examined one such annotation problem involving a conserved Cryptosporidium stress-response candidate protein, CPATCC_0028580_t1 (833 aa). The central question was whether this protein is better interpreted as a member of the p53 family, based on similarity to p53-like DNA-binding domains (PF00870), or as a member of the Sestrin family associated with the PA26 domain.

I explored …

Ai×Life 2026: Advances In Computational Biology Across Scales For Life & Health Sciences, Suma Mohan S., Devika N. T., Pranavathiyani G.

Conference Proceedings

Book of Abstracts of the International Conference, AIxLife 2026: Advances in Computational Biology Across Scales for Life & Health Sciences, held on 17–18 April 2026, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, INDIA 

About the Conference

Conventional computational biology laid the foundation for biological data analysis through statistical models, algorithms, and curated databases, enabling insights into genes, proteins, and pathways. Today, the integration of artificial intelligence, spanning machine learning, deep learning, and large language models (LLMs) is driving a transformative shift across biological scales, from atomic and molecular interactions to pathways, cellular systems, organisms, and populations.

AI-powered approaches …

Quantitative Genetics, Genomics, And Phenomics In Maize And Sorghum, Nikee Shrestha

Complex Biosystems Program: Dissertations and Student Research

Generating the best crop varieties and hybrids requires identifying genes associated with the phenotype of interest and screening thousands of varieties across multiple locations. Quantitative genetics, along with comparative genomics, phenomics, and machine learning approaches, can help us identify target genes associated with the phenotype of interest to develop the right genotypes. Satellite platforms offer logistical and technical advantages in scalability and accessibility and could facilitate plot-level predictions, especially with steadily improving spatial resolution, thereby empowering the large-scale screening of thousands of genotypes across diverse locations. In the first chapter, I evaluated over 20,000 plot-level images of over 80 hybrid …

Investigating The Taxonomic Uncertainties Of Potentilla Rupincola, Natalie Elizabeth Hieber

Master's Theses

Landscape stewardship is an integral role for land managers that becomes more important when rare or endangered species occur within managed areas. Conservation across the landscape is a primary concern for land managers, but resources allocated for conservation can be limited due to many competing goals. Taxonomic uncertainty surrounding rare and endangered taxa, particularly plant taxa, that have historically been classified solely using morphological features further complicates conservation planning. One such taxon is Potentilla rupincola, a rare plant endemic to the eastern Rocky Mountains in Colorado. For over a century, botanists have debated whether P. rupincola is a distinct species …

Non-Destructive Automated Classification Of Human And Large Mammal Long Bone Fragments: A Deep Learning Approach Using Micro-Ct Histomorphology And Grad-Cam Interpretation, Kathleen Marie Kelley

Department of Anthropology: Theses and Student Research

This study explores the development and validation of an automated, deep learning system designed to differentiate human from large mammal long bone fragments using micro-CT imagery. A comprehensive dataset of cross-sectional µCT images was assembled from human and animal skeletal material processed at the DPAA, Nebraska. A convolutional neural network (CNN) based on a ResNet-18 architecture, utilizing transfer learning from ImageNet weights, was trained to classify µCT images as human or animal. The model achieved a mean classification accuracy of 89.85% (± 8.27%) across five sample-level cross-validation folds, with a sensitivity of 96.21% and a 95% bootstrap confidence interval of …

Population Structure And Connectivity Of Atlantic Nurse Sharks (Ginglymostoma Cirratum) In The Bahamas And Outlying Areas, Baylie A. Fadool

School of Natural Resources: Dissertations, Theses, and Student Research

Understanding animal ecosystem dynamics and behavior at the individual and population levels is essential for identifying life-history patterns and important areas for management and conservation. Marine fish species often face minimal geographic barriers to movement, but environmental (temperature, salinity, current) or intrinsic barriers (philopatry, site fidelity) can dictate gene flow. Atlantic nurse sharks (Ginglymostoma cirratum) are an International Union for Conservation of Nature (IUCN) listed ‘vulnerable’ species and present a unique opportunity to investigate patterns of population structure and connectivity in large-bodied sharks. They are benthic and display reproductive philopatry, with recent work suggesting they have the capacity …

Pattern Dynamics And Stochasticity Of Brain Rhythms And Spike Trains In A Tauopathy Mouse Model Of Alzheimer’S Disease, Clarissa M. Hoffman

Dissertations and Theses (Open Access)

Systems neuroscience posits that every aspect of perceived physical reality, every aspect of animal and human behavior, and every cognitive phenomenon emerges from patterns of neuronal activity. While most researchers embrace this idea, there are major difficulties in describing and analyzing these complex neuronal dynamics—spike flows produced by cells ensembles, synchronized extracellular field oscillations, and other patterns—which limits our understanding of how the activity of individual neurons and the whole-animal cognition and behavior might be connected. In particular, we lack the approaches and even the semantics for connecting the individual cell outputs and the integrated results of their activity. Current …

Understanding Epigenomic Landscapes In Cancer Progression And Immunotherapy Response, Jonathan Schulz

Dissertations and Theses (Open Access)

Nonmutational epigenomic reprogramming has emerged as a key hallmark of cancer that plays crucial roles in tumor evolution during its progression and response to therapy. However, the extent and nature of epigenomic reprogramming remains poorly understood. This dissertation examines how epigenetic regulation shapes cancer progression and response to immunotherapy. Working at the intersection of cancer biology and computational genomics, it develops analytical frameworks for characterizing chromatin structure and DNA methylation across diverse tumor contexts and uses these frameworks to address two complementary biological questions: how promoter-associated chromatin organization varies across cancer types, and how epigenetic perturbation modulates tumor immunogenicity in …

Design And Optimization Of Peptide Inhibitors Targeting Kinesin: Molecular Modeling Studies And Virtual Screening For Therapeutic Candidate Development, Maraf Mbah Bake

Open Access Theses & Dissertations

Kinesins are ATP-driven molecular motors essential for intracellular transport and mitotic spindle assembly, and their mechanochemical behavior has been extensively characterized through computational tools. The first project reviews decades of advances in molecular dynamic simulations, including all-atom and coarse-grained molecular dynamics, Markov state models, Brownian dynamics, and free-energy approaches, which have collectively deepened our understanding of conformational transitions, microtubule-binding interfaces, and ligand interactions, especially for the mitotic motor Eg5. The second review examines the rapid emergence of quantum computing as a transformative technology for drug discovery, highlighting key historical milestones, recent progress in hybrid quantum-classical algorithms, quantum-enhanced docking, and quantum …

Growth Hormone Pathway As A Prognostic And Therapeutic Biomarker In Patients With Unresectable Hepatocellular Carcinoma Treated With Radiation Therapy, Joe R Eid, Safa Kaseb, Lianchun Xiao, Ryan Sun, Mahesh Kumar Kannan, Manal Hassan, Asif Rashid, Hop S Tran Cao, Hesham M Amin, Eugene J Koay

Faculty, Staff and Student Publications

Purpose: Radiation therapy (RT) has emerged as an effective local therapy option for patients with unresectable hepatocellular carcinoma (HCC) and is associated with improved overall survival (OS). However, some patients still have poor outcomes after RT, and biomarkers are needed to stratify prognostic groups. High circulating growth hormone (GH) levels promote HCC proliferation and survival and are associated with aggressive disease. In this study, we evaluated whether pretreatment GH levels are associated with OS and progression-free survival (PFS) in patients who underwent RT for unresectable HCC.

Methods and materials: Patients undergoing RT for HCC during 2017-2023 were identified from a …

Potential Impact Of Parasites In The Transmission Of Chronic Wasting Disease, Paulina Soto, Rodrigo Morales

Faculty, Staff and Student Publications

No abstract provided.

Corrigendum To 'Risk Factors For Bronchiolitis Obliterans Syndrome After Initial Detection Of Pulmonary Impairment After Hematopoietic Cell Transplantation' [Transplantation And Cellular Therapy 29/3 (2023) 204-204], Mansour Alkhunaizi, Badar Patel, Luis Bueno, Neel Bhan, Tahreem Ahmed, Muhammad H Arain, Rima Saliba, Gabriela Rondon, Burton F Dickey, Lara Bashoura, David E Ost, Liang Li, Shikun Wang, Elizabeth Shpall, Richard E Champlin, Rohtesh Mehta, Uday R Popat, Chitra Hosing, Amin M Alousi, Ajay Sheshadri

Faculty, Staff and Student Publications

No abstract provided.

Optimized Ultrasound Imaging Of Phase-Change Nanodroplets, Charles R Dyall, Dmitry Nevozhay, Andy Liu, Trevor M Mitcham, George J Lu, Konstantin V Sokolov, Richard R Bouchard

Faculty, Staff and Student Publications

Phase-change nanodroplets (PCNDs) continue to generate significant research interest due to their potential to extravasate into tissue, to be targeted for molecular imaging and drug delivery, and to undergo an induced phase-change to "activated" microbubbles (MBs) for ultrasound (US) imaging. To accurately quantify molecular markers, however, one assumes a consistent proportion of PCNDs in a region of interest (ROI) are stably activated and imaged. Herein we present a framework for developing a diagnostic sequence that is optimized for PCND activation uniformity, contrast, and acquisition time. To develop this framework, activation was examined at three scales of increasing complexity: single, adjacent, …

Characterizing The Molecular Response Of Embryonic Zebra Finch To Acute Sound Playback, Saidat O. Adeniran-Obey Miss

All Theses

Auditory stimuli are important cues that influence developmental plasticity in animals and are important for development and adaptation to an ever-changing environment. In the zebra finch (Taeniopygia guttata), there is evidence of adaptive developmental reprogramming in response to a prenatal ‘heat call’. Embryos exposed to this heat call exhibit changes in growth rate post-hatch, increased heat resistance, and enhanced reproductive success at maturity. However, it has long been assumed that embryonic zebra finches cannot respond to sound due to the immaturity of their auditory system. These findings raise the critical question of whether late-stage zebra finch embryos can, …

Development Of A High-Throughput Framework For Studying Choice-Movement Dynamics In Freely Moving Rats Across Motivational And Pharmacological States, Atanu Giri

Open Access Theses & Dissertations

This thesis develops and applies high-throughput behavioral assays and analysis pipelines to study how external contingencies and internal state shape rodent decision-making. First, it introduces RECORD (Reward-Cost in Rodent Decision-making), a modular platform that combines 3D-printed arenas, microcontroller-based control, and closed-loop trial structure to deliver graded rewards and costs in a foraging-like environment. RECORD supports scalable data collection across multiple arenas and a software stack for parsing, databasing, and extracting spatiotemporal behavioral features and psychometric choice functions. Using this framework, the thesis quantifies how animals integrate sucrose reward magnitude with aversive light cost, revealing structured individual differences and sex-dependent movement …