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

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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 …

Genomic Data Science Approaches For Understanding Human Diseases, Snehal Shah

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The intricate interplay of genetic predisposition, environmental influences, and lifestyle acts as the multifactorial landscape of diseases. Understanding this complexity presents a significant challenge. Molecular insights into disease mechanisms, particularly the interactions of DNA, RNA, and proteins with environmental and lifestyle factors, have revolutionized disease diagnosis, prognosis, and treatment. High-throughput technologies, such as next-generation sequencing, generate large amounts of molecular data, holding a wealth of knowledge. These datasets unveil the roles of genes and their interactions with various factors through analysis, shedding light on previously unknown molecular mechanisms underlying disease pathogenesis. Furthermore, they facilitate the discovery of biomarkers crucial for …

Single Cell Pharmacodynamic Modeling Of Cancer Cell Lines, Arnab Mutsuddy

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Cancer is one of the leading causes of disease related death worldwide. Since the discovery of the genomic origins of cancer, targeted therapy has been developed towards specific mutations implicated for oncogenic transformation. However, current standard-of-care for mapping cancer patients to efficacious drug combination is often inadequate. The pathophysiology of tumor progression relies on the dysregulation of biomolecular pathways of which the topology and the dynamics challenge prognosis. Moreover, the overall genomic instability involved in disease states and the resulting inter-patient as well as intra-tumoral heterogeneity challenge rationalization of therapy and clinical decision-making. It highlights the need for the use …

Acetate Metabolism In The Fungal Pathogen Cryptococcus Neoformans, Oly Ahmed

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Cryptococcus neoformans is an environmental basidiomycetous fungus with a worldwide distribution and a wide range of habitats. Inhalation of the desiccated yeasts or spores of C. neoformans often leads to opportunistic pulmonary infections in immunocompromised individuals, and in severe cases causes lethal meningitis following hematogenous dissemination. During infection, depending on the tissue and disease state, the invading fungi experience a range of nutrient microenvironments within the host body. As a result, rapid metabolic adaptations geared towards efficient utilization of carbon sources alternative to glucose become one of the prime determinants of survival and growth for the pathogen. Incidentally, cryptococcal infection …

Large Genomes Assembly Using Mapreduce Framework, Yuehua Zhang

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Knowing the genome sequence of an organism is the essential step toward understanding its genomic and genetic characteristics. Currently, whole genome shotgun (WGS) sequencing is the most widely used genome sequencing technique to determine the entire DNA sequence of an organism. Recent advances in next-generation sequencing (NGS) techniques have enabled biologists to generate large DNA sequences in a high-throughput and low-cost way. However, the assembly of NGS reads faces significant challenges due to short reads and an enormously high volume of data. Despite recent progress in genome assembly, current NGS assemblers cannot generate high-quality results or efficiently handle large genomes …

Data-Driven Biomarker Panel Discovery In Ovarian Cancer Using Heterogenous Data Fusion On Exosomal And Non-Exosomal Microrna Expression Data, Paritra Mandal

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Ovarian cancer (OC) is an aggressive gynecological cancer and is currently the 5th leading cause of deaths due to cancer in women. High mortality rates are attributable to the vague pathogenesis and asymptomatic nature of the early stages. The development of a liquid biopsy for routine OC screening could help identify the disease at an earlier stage, making treatments more likely to be effective thereby increasing survival rates. Exosomes, small (~100nm) extracellular vesicles present in body fluids, have been shown to contain cancer-progression, onset, and related factors, making them good candidates for use in liquid biopsies. However, to date, only …

Modeling Electrostatics In Molecular Biology And Its Relevance With Molecular Mechanisms Of Diseases, Mahesh Koirala

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Electrostatics plays an essential role in molecular biology. Modeling electrostatics in molecular biology is complicated due to the water phase, mobile ions, and irregularly shaped inhomogeneous biological macromolecules. This dissertation presents the popular DelPhi package that solves PBE and delivers the electrostatic potential distribution of biomolecules. We used the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase and demonstrated that the first-principles method could also model the binding. This dissertation also reflects the use of existing computational approaches to model the effects of Single Amino Acid Variations (SAVs) to reveal molecular mechanisms …

Deciphering Medicago Truncatula Nodulation Using Time-Series Transcriptomic Data At Multiple Levels Of Resolution: Organ, Tissue, And Single-Cell, Yueyao Gao

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Use of chemical nitrogen fertilizers has environmental repercussions such as global warming, soil contamination, and aquatic eutrophication. Legumes form a symbiotic association with nitrogen-fixing bacteria (rhizobia sp.) to obtain atmospheric nitrogen through the formation of a specialized root structure called a nodule. Understanding the transcriptional reprogramming during nodulation is a powerful approach to decipher the genetic control of nodulation, with the goal of engineering nitrogen-fixing symbiosis into non-leguminous crops. This dissertation focuses on the analytics of bulk, tissue-specific, and single-cell RNA-seq technologies and how I utilized them to discover a collection of genes to aid in deciphering nodulation mechanisms in …