Leveraging Attention Mechanism To Unlock Gene And Protein Attributes, Ala Jararweh

Computer Science ETDs

Advancing personalized medicine depends on effectively integrating and interpreting the vast, heterogeneous landscape of biological data, from genomic sequences and transcriptomics to the insights embedded in scientific literature. Current machine learning models often focus on single data modalities, limiting their capacity to capture the multifaceted nature of biological systems. We address this gap by developing three attention-based machine-learning models integrating diverse data modalities. Firstly, DeepVul is a multi-task model that leverages cancer transcriptome data to predict genes critical for cancer survival and their corresponding drugs. Subsequently, LitGene refines gene representations by integrating textual information from the scientific literature. Finally, Protein2Text …

Identification Of Novel Argonaute Proteins Using A Metagenomic Mining Approach, Lobna Abdallah Ghonaim

Theses and Dissertations

Gene editing is one of the most promising tools in science. It enables precise modifications of an organism's genetic material. Metagenomics is considered a powerful tool that unlocks the broad genetic potential found in uncultured microbial communities. Exploring the genetic diversity of uncultured microbial communities helps identify novel functional proteins with unique properties and make the best use of these diverse microbial ecosystems.

We developed and employed a metagenomic-based approach to mine more than 1000 metagenomes for prokaryotic argonaute proteins (pAgos), a potential gene editing machinery encoded in bacterial and archaeal genomes. Our workflow involved strict quality control, sequence assembly, …

Taming Biological Complexity Through The Use Of Symmetries, Luis A. Álvarez-García

Dissertations, Theses, and Capstone Projects

The study of biological systems is, inherently, the study of very complex systems. This is essentially due to the fact that they are made up of numerous, often very complicated, interactions between an extensive number of components. Often necessitating an abundance of quantitative parameters and details for a precise description. The human brain for ex- ample, consisting of ∼ 80 billion neurons with ∼ 800 to 100 trillion connections between them, each of them depending on a large set of parameters. Even simpler examples such as bacterial organisms, such as E. coli and B. subtilis, which we focus on …

Doves And Symbiotic Bacteria: Whole-Genome Assembly And Phylogenomic Inference, Mariam Topchyan

Theses and Dissertations

Part 1

I examined a potential source of variation in phylogenetic inference, investigating whether handling single-nucleotide polymorphisms (SNPs) through different methods during reference-guided genome assembly of pigeon and dove species impacts phylogenetic reconstruction and inference. Specifically, I created a custom consensus base calling tool that handles allelic variation through two different approaches, either ignoring heterozygous sites by denoting them as an ambiguous character “N,” or using a pseudo-random choice between supported base variants. Through reference-guided assembly of 108 dove species, I generated two datasets of alignments using both consensus calling methods, created two trees from both datasets via supermatrix and …

Genomic Epidemiology Of Staphylococcus Aureus Sequence-Type 72, Sachitaa Senthilkumar

Honors Undergraduate Theses

Staphylococcus aureus (S. aureus, SA) is a gram-positive bacterial colonizer and pathogen commonly carried on the skin and in the anterior nares of humans. SA colonization may lead to a variety of non-invasive (e.g., skin and soft tissue infections, SSTIs) and invasive (e.g., bacteremia and osteomyelitis) infections. The SA population is comprised of multiple lineages that can be delineated through multi-locus sequence typing (MLST), which compares nucleotide sequences within seven housekeeping genes. Strains belonging to an MLST share a common evolutionary history and phenotypic characteristics like antibiotic resistance or virulence. As a result, the epidemiology of lineages can be …

Enhancing Clinical Trial Matching In Molecular Diagnostics: Using Natural Language Processing And Clustering Approaches In Hematological Malignancies, Gillian Fanning

Theses and Dissertations

Clinical trial matching is a critical component of personalized medicine, particularly in the management of hematologic malignancies. At Virginia Commonwealth University (VCU) Health, the Molecular Diagnostics (MDX) Lab produces somatic variant reports and recommends clinical trials based on the presence of clinically significant mutations. However, the current manual trial recommendation process is time-intensive and lacks scalability.

This study introduces a computational framework to streamline and standardize clinical trial matching using natural language processing (NLP) and unsupervised clustering. Trial brief descriptions were analyzed to extract frequent terms, and trials were grouped based on term similarity using joint dimensionality reduction and clustering. …

Foundation Models In Bioinformatics, Fei Guo, Renchu Guan, Yaohang Li, Qi Liu, Xiaowo Wang, Can Yang, Jianxin Wang

Computer Science Faculty Publications

With the adoption of foundation models (FMs), artificial intelligence (AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges, such as pre-training frameworks, model evaluation and interpretability. FMs demonstrate notable proficiency in managing large-scale, unlabeled datasets, because experimental procedures are costly and labor intensive. In various downstream tasks, FMs have consistently achieved noteworthy results, demonstrating high levels of accuracy in representing biological entities. A new era in computational biology has been ushered in by the application of FMs, focusing on both general and specific biological issues. In this review, we introduce recent advancements in bioinformatics FMs …

Computational Tools For Protein Classification In Metagenomes, Fawad Ullah

Dissertations, Master's Theses and Master's Reports

Advances in genomic sequencing have dramatically increased the amount and the speed at which genomic data is being generated. These technological advances have enabled the ability to profile the genetic information of organisms and communities at unprecedented scales. Many methods have been developed to identify and classify genes within these datasets. However, many generic pipelines for gene annotation struggle to accurately predict specific protein classes that may not be represented in their databases. Two major challenges exist for classification of specific protein classes in metagenomic databases. The first is the fact that many metagenomic assemblies are highly fragmented with many …

Characterizing Somatic Variants In Nanopore Data With Machine Learning, Shwethal Sayeeram Trikannad

Master's Projects

Oxford Nanopore Technology (ONT) is a popular long-read sequencer in genomics. However, its high base-calling error rate produces several sequencing artifacts. Detection of somatic variants in ONT sequenced tumor-normal samples remains challenging due to low frequencies. In this study, machine learning was applied to a dataset created by benchmarking ClairS output against HCC1395 and colo829 truth sets to classify variants and artifacts. Relevant features were engineered from sequence context and variant site characteristics to model artifact profiles. HistGradientBoostingClassifier achieved 0.876950 accuracy, outperforming all other models. Variant quality was the top predictor with an aggregate accuracy of over 85%. This work …

Phylogenetic Analysis Of Metabolic Enzymes In Hypoxic/Anoxic Conditions In Cetaceans And Cancer, Samerna A. Masih

Electronic Theses & Dissertations (2024 - present)

Cancer cells often exhibit a Warburg-like metabolism, which includes increased fatty acid synthesis and storage that help them survive in hypoxic conditions. This shift is marked by the heightened synthesis and accumulation of fatty acids, acting as a survival mechanism in low-oxygen environments (Baumann et al., 2016). Interestingly, deep-diving whales may utilize a similar metabolic pathway to produce wax esters during their prolonged dives.

Our study focused on exploring the genetic and metabolic similarities between breast cancer cells and deep-diving whales, using computational analyses to investigate lipid metabolism genes. We looked for evolutionarily conserved variations that might reveal adaptive mechanisms …

Timigp: A Computational Framework To Determine The Tumor Immune Microenvironment Associated With Prognosis And Immunotherapy Response, Chenyang Li

Dissertations and Theses (Open Access)

Accumulating evidence has suggested that the tumor immune microenvironment (TIME) drastically impacts cancer patients’ clinical outcomes, including prognosis and immunotherapy response. However, understanding TIME remains challenging due to its complexity and heterogeneity. In this dissertation, we introduce TimiGP (Tumor Immune Microenvironment Illustration based on Gene Pairs), a computational framework designed to address this challenge. Leveraging single-cell RNA-seq (scRNA-seq) and bulk gene expression data alongside clinical information, TimiGP constructs a cell-cell interaction network that elucidates the relationship between immune cell function and relevant clinical outcomes, such as prognosis and treatment response. With immunological insights, these cell-cell interactions also facilitate the development …

Exercise Therapy Rescues Skeletal Muscle Dysfunction And Exercise Intolerance In Cardiometabolic Hfpef, Heather Quiriarte, Robert C. Noland, James E. Stampley, Gregory Davis, Zhen Li, Eunhan Cho, Youyoung Kim, Jake Doiron, Guillaume Spielmann, Sujoy Ghosh, Sanjiv J. Shah, Brian A. Irving, David J. Lefer, Timothy D. Allerton

School of Graduate Studies Faculty Publications

Exercise intolerance, a hallmark of heart failure with preserved ejection fraction (HFpEF) exacerbated by obesity, involves unclear mechanisms related to skeletal muscle metabolism. In a “2-hit” model of HFpEF, we investigated the ability of exercise therapy (voluntary wheel running) to reverse skeletal muscle dysfunction and exercise intolerance. Using state-of-the-art metabolic cages and a multiomic approach, we demonstrate exercise can rescue dysfunctional skeletal muscle lipid and branched-chain amino acid oxidation and restore exercise capacity in mice with cardiometabolic HFpEF. These results underscore the importance of skeletal muscle metabolism to improve exercise intolerance in HFpEF.

Investigating The Rare Aneuploid Cells In Normal Breast And Therapeutic Resistance In Triple Negative Breast Cancer Using Single Cell Genomics, Yiyun Lin

Dissertations and Theses (Open Access)

Aneuploid epithelial cells are common in breast cancer, however their presence in normal breast tissues is not well understood. To address this question, we applied single cell DNA sequencing to profile copy number alterations (CNAs) in 83,206 epithelial cells from breast tissues of 49 healthy women and single cell DNA&ATAC co-assays to 19 women. Our data shows that all women harbored rare aneuploid epithelial cells (median 3.19%) that increased with age. Many aneuploid epithelial cells (median 82.22%) in normal breast tissues underwent clonal expansions and harbored CNAs reminiscent of invasive breast cancers (gains of 1q, losses of 10q, 16q and …

Quantifying Effects Of Partial Genetic Backgrounds To Decode Genetic Drivers Of Clinical Phenotypes, Rini Pauly

All Dissertations

Understanding partial genetic backgrounds illuminates the genetic architecture of complex traits and diseases, revealing how diverse genetic backgrounds contribute to phenotypic diversity. With this approach we could advance personalized medicine by identifying population-specific variants affecting drug metabolism, tailoring medical treatments to individual genetic profiles. Additionally, it offers evolutionary insights into human history, shedding light on past migrations and the spread of genetic traits. This research leverages cutting-edge statistical genetics techniques and novel machine learning approaches to efficiently analyze extensive population genomic datasets, distilling complex admixture signals into meaningful genetic markers.

The study introduces Admix-AI, an innovative convolutional neural network-based tool …

The Impact Of Temperature And Humidity On The Transcriptome Of Symbiochloris Reticulata In Relation To Lobaria Pulmonaria’S Genepools, Ioana Violeta Ardelean, Christoph Scheidegger, Mihai Miclaus

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

The Influence Of Environmental Change On Genetic Diversity Across Spatial And Taxonomic Scales, Connor M. French

Dissertations, Theses, and Capstone Projects

The spatial distribution of genetic diversity is of interest to biodiversity scientists and conservationists and is a fundamental metric of biodiversity. Genetic diversity patterns across spatial and taxonomic scales contain information about population and assemblage dynamics that can convey their resilience to environmental change. Ectotherms are especially linked to their environments and may be especially sensitive to fluctuations in the environment over time. Herein, I investigate global and regional patterns of genetic diversity in two groups of ectotherms, insects and lizards, to understand the relationship between environmental change and genetic diversity, from populations to assemblages. Overall, my research aims to …

Early Onset Alzheimer’S Disease Markers In Mouse Hippocampus Unveiled By Single-Cell Transcriptomic Analysis Following Cranial Radiotherapy, Tuba Aksoy

Dissertations and Theses (Open Access)

Cranial radiation therapy plays an integral role in the treatment of brain tumors but can lead to progressive cognitive deficits in survivors by mechanisms that are poorly understood. To develop preventive or mitigative strategies, it is crucial to better understand the underlying pathogenesis of radiation-induced cognitive impairments. The study investigated single-cell transcriptomics and DNA methylation changes as potential drivers of persistent cellular dysfunction after radiation exposure, specifically concentrating on the CA1-3 regions of the hippocampus and the prefrontal cortex due to their role in cognitive functions. Thirteen-week-old mice underwent whole-brain radiation at clinically relevant doses. Following whole-brain radiation, an assessment …

Utilizing The In4mer Crispr/Cas12a Multiplex Knockout Platform To Investigate Synthetic Lethality In The Human Genome, Xingdi Ma

Dissertations and Theses (Open Access)

The emergence of high-throughput sequencing technologies and the development of targeted cancer therapies have significantly advanced our understanding of cancer genomics and prolonged patient survival. Despite these advances, durable response remains difficult to achieve in the clinic. The concept of synthetic lethality has gained traction as a promising opportunity to discover novel cancer-specific vulnerabilities and therapeutic targets. Unfortunately, initial technologies for combinatorial genetic perturbation in mammalian cells suffer from inefficiency and are challenging to scale. In this dissertation, I report: 1) paralog selection method to select candidate synthetic lethal paralogs; 2) our Cas12a multiplex platform “IN4MER” that provides superior sensitivity …

Evolution And Adaptation To Temperature In Thermotogota, Anne Amelia Farrell

Dartmouth College Ph.D Dissertations

Life thrives across incredibly diverse environmental conditions, yet most organisms are restricted to growing within a narrow range around their optimum growth temperature (OGT). The evolutionary events leading to changes in OGT are poorly understood, and it is uncertain if specific genes are required to thrive at a particular temperature. The bacterial phylum Thermotogota is an excellent model for the evolution of OGT. It comprises mesophilic, thermophilic, and hyperthermophilic members that collectively grow between 20°C and 90°C.

In this work, I analyze the history of OGT in the Thermotogota phylum and show how horizontal gene transfer contributes to the evolution …

Omani Camels From A Cultural And Genomics Perspective, Al Muatasim Al Zadjali

Electronic Theses and Dissertations

The Dromedarian camel, Camelus dromedarius, is native to the Arabian Peninsula, including the Sultanate of Oman. These camels are used for food, milk, as well as show and racing competitions. Despite their economic and cultural importance research on camels in Oman is limited. The goal of this study was to examine their genomic variation, relationship with camels in other parts of the Arabian Peninsula, and to determine if selective breeding has led to the establishment of distinct breeds in Oman. Information was compiled from multiple sources to produce a comprehensive review on the breeding, management, economic and cultural use, …

Mismatch Repair Deficient Neoantigen And Associated Circulating T-Cell Receptor Repertoires In Lynch Syndrome, Ana Bolivar

Dissertations and Theses (Open Access)

Lynch Syndrome (LS) is the most common inherited colorectal cancer (CRC) syndrome. It constitutes the perfect model to understand DNA mismatch repair deficient (MMRd) carcinogenesis, which underlies 15% of early-stage CRC. LS patients develop MMRd tumors with high loads of shared neoantigens (neoAgs), which are recognized by the immune system. Previous research has concentrated on discovering neoAgs and their potential as targets for vaccines in LS patients. However, these studies have primarily identified shared neoAgs from cancers, lacking detailed information on targetable neoAgs present in precancerous lesions. Understanding this landscape of pre-cancer derived neoAgs is crucial for intercepting cancer development …

The In4mer Crispr/Cas12a Multiplex Knockout Platform And Its Applications, Nazanin Esmaeili Anvar

Dissertations and Theses (Open Access)

Discovering synthetic lethal interactions between genes holds the key to uncovering cancer vulnerabilities, enabling the development of more effective drugs for patients. However, identifying these vulnerabilities in the complex genome of human, which comprises thousands of genes, poses a significant challenge. One alternative approach to investigate these interactions involves exploring enriched sources of synthetic lethal interactions, such as paralog pairs. In recent years, a couple of studies have conducted dual-gene knockout experiments on paralog pairs using different approaches to identify synthetic lethal interactions. In this study, we conducted a meta-analysis of CRISPR genetic interaction screens. We identified a candidate set …

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 …

Parental Environnement Influences Offspring Gene Expression In The Olympia Oyster, Ostrea Lurida., Mark S. Yeats

LSU Master's Theses

The Olympia Oyster is the only native oyster species on the Pacific coast of North America. Seasonality in water temperatures across this threatened species’ broad and fragmented range has been linked to its development, reproductive timing, reproductive activity, growth, and survival rates. Recent evidence suggests parental environments can have carry-over effects on larval growth and respiration rates in response to temperature. In this study, we utilized transcriptomic methods to identify the underlying mechanisms of this cross-generation plasticity. Sequence libraries of adult ctenidia tissue and pooled larval replicates were extracted and spawned from hatchery raised oysters of the same parentage immediately …

Coral Scar Investigation: An Application Of Machine Learning And Computational Biology Methods To Understand Coral Holobiont Response To Various Tissue Loss Diseases, Emily W. Van Buren

Biology Dissertations - Archive

Coral disease is one of the biggest challenges facing coral reefs that actively changes biodiversity resulting in coral decline. With the rising threat of diseases, corals require biomarkers that reflect the immune systems and differences between common coral tissue loss diseases to best assist in coral restoration efforts. To obtain these biomarkers, my dissertation leverages two previously published datasets from two tissue loss disease exposure studies to investigate genes that are relevant for coral immune pathways, disease susceptibility, and classification between the diseases. In Chapter 2, I use comparative computational biology tools and protein assays to identify the melanin cascade …

Corals In Crisis: A Transcriptomic Investigation Of Stony Coral Tissue Loss Disease, Kelsey M. Beavers

Biology Dissertations - Archive

Coral reefs face existential threats due to climate change and human activities. The combined effects of ocean warming, overfishing, pollution, and habitat destruction have fundamentally altered the functionality of coral reefs and are driving a drastic increase in the prevalence and severity of coral disease outbreaks. Stony coral tissue loss disease (SCTLD) has emerged one of the most devastating disturbances to Caribbean reef ecosystems on record. Despite notable progress, the cellular mechanisms driving SCTLD pathogenesis remain poorly understood. To address this issue, my dissertation investigates the gene expression, histopathology, immune protein activity, and symbiont community dynamics involved in SCTLD progression …

Exploring 3d Genome Interaction And Epigenetic Regulation Via Swi/Snf Complex And Deep Learning Models, Ruoyun Wang

Dartmouth College Ph.D Dissertations

The three-dimensional organization of the genome is fundamental in regulating gene expression and maintaining cellular function. This organization's complexities, influenced by epigenetic marks and chromatin remodeling complexes, are crucial for understanding genomic regulation. Among these, the SWI/SNF complexes are key, facilitating chromatin accessibility and regulating gene activity across cell types. The first part of my dissertation focuses on SWI/SNF complexes, exploring their role in chromatin remodeling and their impact on 3D genome architecture. Utilizing next-generation sequencing (NGS) techniques, this section investigates the interplay between these complexes and chromatin structure. During my research on the SWI/SNF complex, I was intrigued by …

The Evolution Of The Metazoan Circadian Molecular Mechanism And The Conservation Of Canonical Circadian Elements, Olivia Waldridge

Theses and Dissertations--Biology

The temporal organization of biological activities through circadian rhythms is pivotal for the survival of organisms. Significant progress has been made in understanding the molecular foundations of animal circadian clocks through the characterization of key components such as Clock, Bmal1/Cycle(Cyc), Period (Per), Timeless, and Cryptochrome (Cry) in several model organisms. To determine the universality of this conservation, we investigated the sequences of these genes and their paralogs across 46 animal species that encompass multiple phyla in the metazoan kingdom to resolve the relative timing of duplication and loss events that have diversified core clock components in the metazoan kingdom. Using …

From Code To Crops: Harnessing Bioinformatics And Artificial Intelligence (Ai) In Agricultural Omics, Lakshay Anand

Theses and Dissertations--Plant and Soil Sciences

Global agricultural faces numerous challenges, such as climate change, resource limitations, novel pests and diseases, increasing costs, and the ever-increasing human population. To tackle these challenges, we need innovative strategies that combine new technologies and data analytics approaches to enhance agricultural output, promote sustainable methods, and optimize resource allocation. The key to this innovation lies in understanding the complex molecular web within plants that governs their growth, defense, and adaptability mechanisms. By mastering this molecular network, we can cultivate crops that are more resilient, sustainable, and suitable for different climatic terrains. Moreover, studying the symbiotic relationship between plants and microorganisms …

Machine Learning And Rna Bioinformatics, Jason Rafe Miller

Graduate Theses, Dissertations, and Problem Reports (ETD)

The applied science of bioinformatics encompasses computational analysis of molecular biology data. Advances in genomics and DNA sequencing technology have enabled computational analysis of ribonucleic acids (RNAs), which play diverse and critical roles in most cells. To assist the study of human RNA, we trained machine learning models on RNA nucleotide sequences, devoid of domain knowledge. We built models that distinguish long non-coding lncRNA from protein-coding mRNA, and models that predict the cytoplasmic vs. nuclear preferences of lncRNAs. In a review of published lncRNA subcellular localization classifiers, we show that the commonly used validation protocol generates optimistic performance measures, and …