Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"University of Washington" +contributor:("Price, Nathan D"). Showing records 1 – 2 of 2 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


University of Washington

1. Pearl, Jocelynn Renee. Systems genomics approaches in neurologic disease.

Degree: PhD, 2018, University of Washington

Neurologic disorders encompass a broad range of diseases including neurodegenerative (Huntington's disease, Parkinson's disease, Alzheimer's), neurodevelopmental (Autism, Rett syndrome), and psychiatric or mental disorders (Schizophrenia, bipolar disorder). Changes in brain gene expression accompany many of these disorders as demonstrated in studies of human post-mortem tissue. A critical objective in our understanding of gene misregulation in neurologic diseases, which range in heritability, is a comprehensive characterization of the spatial and temporal dynamics of the associated changes and how gene regulatory drivers mediate them. In this work, I explore early gene expression changes in a longitudinal study of Huntington’s disease (HD) mouse models, and survey gene networks enriched for differential gene expression. I go on to investigate the contributions of sequence-specific transcription factors (TFs) to disease-specific gene expression change in HD and psychiatric disorders. I begin with a genome-scale model for TF-target gene interactions by combining publicly available DNase-seq footprinting and brain transcriptomic datasets. Using this transcriptional regulatory network (TRN), we identified TFs whose predicted target genes were overrepresented among differentially expressed genes in neurologic disorders. Following the identification of these predicted driver TFs, I applied multiple functional genomics approaches to characterize their genome-wide binding sites (ChIP-seq), survey the impact of TF overexpression or knockdown (overexpression or CRISPR-Cas9-mediated editing), and assess the functional consequences of variation present in a motif instance (luciferase reporter assay). Together the findings from these studies further our understanding of the functional networks of genes and TFs implicated in neurologic disease and provide a methodological framework for future applications beyond the diseases covered in this thesis. Advisors/Committee Members: Price, Nathan D (advisor), Hood, Leroy (advisor).

Subjects/Keywords: gene regulation; Huntington's disease; network biology; neurologic disease; Systems biology; transcription factor; Molecular biology; Neurosciences; Genetics; Molecular and cellular biology

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pearl, J. R. (2018). Systems genomics approaches in neurologic disease. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40943

Chicago Manual of Style (16th Edition):

Pearl, Jocelynn Renee. “Systems genomics approaches in neurologic disease.” 2018. Doctoral Dissertation, University of Washington. Accessed May 08, 2021. http://hdl.handle.net/1773/40943.

MLA Handbook (7th Edition):

Pearl, Jocelynn Renee. “Systems genomics approaches in neurologic disease.” 2018. Web. 08 May 2021.

Vancouver:

Pearl JR. Systems genomics approaches in neurologic disease. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/1773/40943.

Council of Science Editors:

Pearl JR. Systems genomics approaches in neurologic disease. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/40943


University of Washington

2. Earls, John Carl. Quantifying wellness and disease with personal, dense, dynamic data clouds.

Degree: PhD, 2021, University of Washington

Precision Medicine, where medical treatment is guided by deep molecular knowledge of the individual, has gained momentum in recent years. Rapid advancement in biological measurement technologies such as genome sequencing, mass spectrometry, protein capture assays, microfluidics and quantified-self devices provide an unprecedented opportunity to quantify, explain, and affect each person's health. The key challenge now is how to utilize these new capabilities to maximize wellness and prevent disease. These developments are concurrent with and aided by the increased availability of robust data analytic tools and cheap, scalable computation. In this dissertation, I present three steps taken to advance Precision Medicine. I present the first large multi-omic wellness study, where information from these -omics were integrated and used to provide personalized wellness guidance through a trained wellness coach. I present a holistic and modifiable wellness marker based on aging, generated from longitudinal multi-omic data. Finally, I apply systems approaches with dense phenotypic longitudinal data to profiling cancer, highlighting one approach to personalized 'N of 1' medicine. The research I present in this dissertation has led to the formation of two companies, so far. Advisors/Committee Members: Price, Nathan D (advisor), Ruzzo, Walter L (advisor).

Subjects/Keywords: Computational Biology; Multi-omics; Systems Biology; Computer science; Bioinformatics; Medicine; Computer science and engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Earls, J. C. (2021). Quantifying wellness and disease with personal, dense, dynamic data clouds. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/46767

Chicago Manual of Style (16th Edition):

Earls, John Carl. “Quantifying wellness and disease with personal, dense, dynamic data clouds.” 2021. Doctoral Dissertation, University of Washington. Accessed May 08, 2021. http://hdl.handle.net/1773/46767.

MLA Handbook (7th Edition):

Earls, John Carl. “Quantifying wellness and disease with personal, dense, dynamic data clouds.” 2021. Web. 08 May 2021.

Vancouver:

Earls JC. Quantifying wellness and disease with personal, dense, dynamic data clouds. [Internet] [Doctoral dissertation]. University of Washington; 2021. [cited 2021 May 08]. Available from: http://hdl.handle.net/1773/46767.

Council of Science Editors:

Earls JC. Quantifying wellness and disease with personal, dense, dynamic data clouds. [Doctoral Dissertation]. University of Washington; 2021. Available from: http://hdl.handle.net/1773/46767

.