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Browsing by Author "Kang, Brian"

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    Deconstructing Gustav Mahler's Letters Through Topic Modeling

    (2017-4-18) Kang, Brian; Willan, Claude

    Gustav Mahler’s symphonies mark a critical shift from the Romantic era to the Con- temporary era. Mahler’s symphonies capture complex sentiments that often assume the dramatism of the Romantic era, as well as a more progressive, avant-garde aspects of the contemporary era. However, it is not just Mahler’s music that embraces this very complexity: Mahler himself has lived quite an eventful life which stems from, as well as leads to, his profound character. This thesis aims to gain a closer look into Mahler’s colorful character by analyzing his letters to his wife. Having been a prolific writer, Mahler has written 350 letters to Alma throughout the years of their relationship, which leaves abundant resources to study. This research will analyze the letters in order to gain a deeper understanding into Mahler’s sentiments and his complex psychology to deconstruct Mahler using quantitative methods rather than the traditional qualitative means.

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    Multiplexed Differential Gene Expression Analysis Using CRISPR-Cas Systems

    (2022-08-09) Kang, Brian; Myhrvold, Cameron A; Ploss, Alexander

    Quantification of mRNA expression levels and differential analyses that observe changes in mRNA expression are key in providing insights into biological processes. Today, the gold standard of differential gene expression analysis involves an initial genome-wide screen of expression changes using RNA-Seq, an expensive procedure that has a multiple-week turnaround time for results, and subsequent analyses of specific genes identified through RNA-Seq using the faster and less expensive technique of qPCR. While this workflow allows for effective analysis of changes in gene expression in small sets of key genes, it is too cumbersome for analyzing a larger set of genes or treatment conditions. This project sought to develop a highly multiplexed method of mRNA quantitation using CRISPR-Cas systems and microfluidics devices to parallelize thousands of detection reactions in a single experimental run. Core experimental components such as divalent metal cation concentrations and T7 promoter regions were systematically optimized to maximize the dynamic range of Cas-based quantitation and to improve the limits of quantitation. The developed system was used to quantify changes in transcript levels in yellow-fever-infected human hepatoma cells. These results were compared with gold-standard qPCR results and a strong correlation was observed between Cas-based quantitation and qPCR quantitation.

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