Bioinformatics Commons^™

Dna Methylation-Based Epigenetic Biomarkers In Cell-Type Deconvolution And Tumor Tissue Of Origin Identification, Ze Zhang

Dartmouth College Ph.D Dissertations

DNA methylation is an epigenetic modification that regulates gene expression and is essential to establishing and preserving cellular identity. Genome-wide DNA methylation arrays provide a standardized and cost-effective approach to measuring DNA methylation. When combined with a cell-type reference library, DNA methylation measures allow the assessment of underlying cell-type proportions in heterogeneous mixtures. This approach, known as DNA methylation deconvolution or methylation cytometry, offers a standardized and cost-effective method for evaluating cell-type proportions. While this approach has succeeded in discerning cell types in various human tissues like blood, brain, tumors, skin, breast, and buccal swabs, the existing methods have major …

Tracing Evolution Of Gene Transfer Agents Using Comparative Genomics, Roman Kogay

Dartmouth College Ph.D Dissertations

The accumulating evidence suggest that viruses and their components can be domesticated by their hosts, equipping them with convenient molecular toolkits for various functions. One of such domesticated system is Gene Transfer Agents (GTAs) that are produced by some bacteria and archaea. GTAs morphologically resemble small phage-like particles and contain random fragments of their host genome. They are produced only by a small fraction of the microbial population and are released through a lysis of the host cell. Bioinformatic analyses suggest that GTAs are especially abundant in the taxonomic class of Alphaproteobacteria, where they are vertically inherited and evolve …

Genome-Scale Methylation Analysis In Blood And Tumor Identifies Immune Profile, Age Acceleration, And Dna Methylation Alterations Associated With Bladder Cancer Outcomes, Ji-Qing Chen

Dartmouth College Ph.D Dissertations

Bladder cancer patients receive frequent screening due to the high tumor recurrence rate (more than 60%). Nowadays, the conventional monitoring method relies on cystoscopy which is highly invasive and increases patient morbidity and burden to the health care system with frequent follow-up. As a result, it is urgent to explore novel markers related to the outcomes of bladder cancer. Immune profiles have been associated with cancer outcomes and may have the potential to be biomarkers for outcomes management. However, little work has been conducted to investigate the associations of immune cell profiles with bladder cancer outcomes. Here, I utilized the …

Cell-Typing And Interaction Analysis Of The Immune Compartment Of The Tumor Microenvironment Using High-Resolution Omics Modalities, Courtney Taylor Schiebout

Dartmouth College Ph.D Dissertations

Single-cell RNA-sequencing (scRNA-seq) has provided a new frontier for the investigation of complex tissues. One ideal candidate for the utilization of this method is the tumor microenvironment (TME). The TME is often host to a complex set of cell populations and behaviors that can be highly influential for cancer inhibition or progression. This is especially true of the immune compartment of the TME: the presence of certain types of immune cells in the TME and their expression profiles can significantly affect cancer prognosis in some cases. By providing individual cell-level gene expression data, scRNA-seq can be highly informative for characterizing …

Deep Learning Methods For Prediction Of And Escape From Protein Recognition, Bowen Dai

Dartmouth College Ph.D Dissertations

Protein interactions drive diverse processes essential to living organisms, and thus numerous biomedical applications center on understanding, predicting, and designing how proteins recognize their partners. While unfortunately the number of interactions of interest still vastly exceeds the capabilities of experimental determination methods, computational methods promise to fill the gap. My thesis pursues the development and application of computational methods for several protein interaction prediction and design tasks. First, to improve protein-glycan interaction specificity prediction, I developed GlyBERT, which learns biologically relevant glycan representations encapsulating the components most important for glycan recognition within their structures. GlyBERT encodes glycans with a branched …

Characterization Of Cell Type-Specific Molecular Heterogeneity In Cancer Using Multi-Omic Approaches, Min Kyung Lee

Dartmouth College Ph.D Dissertations

Tumors are composed of heterogeneous cell types each with its own unique molecular profiles. Recent advances in single cell genomics technologies have begun to increase our understanding of the molecular heterogeneity that exists in tumors with particular focus on gene expression and chromatin accessibility profiles. However, due to limitations in methods for certain sample types and high cost for single cell genomics, bulk tumor molecular profiling has been and remains widely used. In addition, other facets of single cell epigenomic profiling, particularly methylation and hydroxymethylation, remains underexplored. Thus, investigations to understand the cell type specific epigenetic heterogeneity and the cooperation …

Multi-Omic And Single-Cell Characterization Of A 3d Skin-Like Tissue Model Of Systemic Sclerosis With A Focus On Epigenetics, Tamar R. Abel

Dartmouth College Ph.D Dissertations

Systemic sclerosis (SSc) is a rare fibrotic autoimmune disease with high mortality and limited FDA approved therapies. Clinical concordance among twins is low; however, a modest familial heritability implicates complex interactions between polygenic risk alleles and the environment as causal – interactions that are mediated by epigenetics. Although mechanisms of tissue fibrosis have been successfully identified and targeted in established in vitro models for SSc, these molecules have ultimately failed in clinical trials. This likely reflects the lack of a reliable in vitro model that faithfully recapitulates the disease.

I utilized a 3D skin-like tissue model to study SSc skin …

The Roles Of Epithelial–Mesenchymal Plasticity In Tumor Heterogeneity, Metastasis, And Patient Survival In Breast Cancer, Meredith Septer Brown

Dartmouth College Ph.D Dissertations

The Epithelial-to-Mesenchymal transition, a critical cellular process in development, is frequently co-opted by solid tumors to promote invasion and metastasis. In particular, the hybrid or intermediate EMT state, possessing both epithelial and mesenchymal characteristics, is associated with increased cancer stemness and plasticity. Similarly, intra-tumoral heterogeneity in solid tumors, in particular breast cancer, is associated with poor prognosis, tumor growth, proliferation, drug resistance, and metastasis. We sought to understand the link between the generation of intra-tumoral heterogeneity and the intermediate EMT state and their impact on tumor progression and patient prognosis. As part of my thesis work, I developed a model …

Deciphering Taxa-Function Relationships In Population-Level Studies Of Human Gut Microbiomes, Quang P. Nguyen

Dartmouth College Ph.D Dissertations

The human gut microbiome is a complex and dynamic ecosystem, featuring a multitude of microbes all interacting with their hosts in an elaborate manner. Even though this exchange is often mediated through microbial metabolic and functional outputs, such as the production of certain metabolites, environmental exposures, and host lifestyle are highly influential in shaping the presence of microbial species irrespective of their individual roles. As such, a comprehensive understanding of the microbiome requires researchers to examine the relationship between taxonomic abundance and function simultaneously. Assessing microbial contributions to important ecosystem services can enable identification of robust functions supported by a …

Discretized Geometric Approaches To The Analysis Of Protein Structures, John Holland

Dartmouth College Ph.D Dissertations

Proteins play crucial roles in a variety of biological processes. While we know that their amino acid sequence determines their structure, which in turn determines their function, we do not know why particular sequences fold into particular structures. My work focuses on discretized geometric descriptions of protein structure—conceptualizing native structure space as composed of mostly discrete, geometrically defined fragments—to better understand the patterns underlying why particular sequence elements correspond to particular structure elements. This discretized geometric approach is applied to multiple levels of protein structure, from conceptualizing contacts between residues as interactions between discrete structural elements to treating protein structures …