Computational Analysis of Cancer Genomic Evolution and Human Endogenous Double-stranded RNA

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dc.contributor.advisorKimmel, Marek
dc.creatorChen, Yujie
dc.date.accessioned2024-01-22T21:20:20Z
dc.date.available2024-01-22T21:20:20Z
dc.date.created2023-12
dc.date.issued2023-10-10
dc.date.submittedDecember 2023
dc.date.updated2024-01-22T21:20:20Z
dc.descriptionEMBARGO NOTE: This item is embargoed until 2025-12-01
dc.description.abstractThe development of next generation sequencing (NGS) technologies has allowed rapid and cost-effective sequencing of large amounts of DNA or RNA, enabling systematic analysis of biological and pathological processes. Interpretation of genomic and transcriptomic data became crucial in both research and clinical settings, particularly for investigating complex human diseases. This thesis employed various computational analysis methods in three projects that utilized different types of NGS data: (1) Constructing genomic trajectory for the progression process of multiple hematopoietic malignancies using panel sequencing and karyotype data; (2) Mathematical modeling of the mutation accumulation history in bladder cancer on a whole-organ level; and (3) Identifying endogenous immunogenetic double-stranded RNA species by classic bioinformatic analysis of RNA-seq data. The research conducted in this thesis revealed genomic evolution dynamics in cancer development providing important reference for cancer progression monitoring and intervention, and shed light on RNA therapeutic targets in autoimmune diseases.
dc.embargo.lift2025-12-01
dc.embargo.terms2025-12-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationChen, Yujie. "Computational Analysis of Cancer Genomic Evolution and Human Endogenous Double-stranded RNA." (2023). Master's thesis, Rice University. https://hdl.handle.net/1911/115339
dc.identifier.urihttps://hdl.handle.net/1911/115339
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectCancer Genomics
dc.subjectComputational Analysis
dc.subjectRNA
dc.subjectSystems Biology
dc.titleComputational Analysis of Cancer Genomic Evolution and Human Endogenous Double-stranded RNA
dc.typeThesis
dc.type.materialText
thesis.degree.departmentSystems, Synthetic and Physical Biology
thesis.degree.disciplineSystems/Synthetic/Phys Biology
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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