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dc.contributor.advisorLyons, Eric H.
dc.contributor.authorHaug-Baltzell, Asher
dc.creatorHaug-Baltzell, Asher
dc.date.accessioned2018-06-28T00:52:39Z
dc.date.available2018-06-28T00:52:39Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10150/628182
dc.description.abstractPerhaps the most influential and pivotal discovery in biology was that genomes, the organism- specific DNA transmitted generation-to-generation, are the foundational “code of life” which contain the instructions necessary to form each and every living organism. Today, the rapid advancement of genome sequencing technology is providing scientists in many disciplines with an unprecedented toolkit for deep insights into how this code generates and maintains life on earth. It is upon this technical toolkit – the ability to decode genomic information – which this dissertation is built. This dissertation is not intended to answer a single question, but rather to highlight three original research articles in the field of comparative genomics and provide additional discussion into how they were enabled by a scientific training focused on building computational thinking and skills in addition to learning topical background knowledge. My goal here is multifaceted; primarily, I aim to help advance our scientific understanding of how evolution has shaped modern genomes, but in this process, I hope to also inspire my fellow scientists to more deeply integrate computational thinking into their biological research. The included articles cover a broad range of topics, yet all stem from the unifying question “how can we effectively and efficiently compare genomes against each other, and what can we learn by performing these comparisons?”. Following a narrative introduction discussing the impact of genome sequencing technology on the field of biology and science as a whole (Chapter 1), a series of chapters guide the reader through three original research manuscripts. These manuscripts cover the development of a comparative genomics tool (Chapter 2), the discovery of an interesting aspect of dopamine receptor evolution (Chapter 3), and the dissection of a set of proposed genomic predictors in human disease treatment (Chapter 4). Next, a white paper styled discussion chapter investigates two specific aspects of computational thinking which are especially relevant to scientific researchers, especially in an era defined by “big data” (Chapter 5). The final conclusion (Chapter 6) ties the distinct parts together into a cohesive message, poses some thoughts on the future of genomic research, and discusses some of the ethical implications which stem from our growing knowledge of the genome.en_US
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectbioinformaticsen_US
dc.subjectcomparative genomicsen_US
dc.subjectdopamine receptor evolutionen_US
dc.subjectevolutionen_US
dc.subjectplacebo effecten_US
dc.subjectsyntenyen_US
dc.titleGenomic Insights: Comparative Genomics in the Big Data Ageen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberSanderson, Michael J.
dc.contributor.committeememberMcCarthy, Fiona M.
dc.contributor.committeememberMerchant, Nirav C.
dc.description.releaseRelease after: 15-May-2020en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineGeneticsen_US
thesis.degree.namePh.D.en_US


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