Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2018.

Bibliographic Details
Main Author: Kedaigle, Amanda Joy
Other Authors: Ernest Fraenkel.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/119026
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author Kedaigle, Amanda Joy
author2 Ernest Fraenkel.
author_facet Ernest Fraenkel.
Kedaigle, Amanda Joy
author_sort Kedaigle, Amanda Joy
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description Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2018.
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spelling mit-1721.1/1190262019-04-10T23:52:52Z Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease Kedaigle, Amanda Joy Ernest Fraenkel. Massachusetts Institute of Technology. Computational and Systems Biology Program. Massachusetts Institute of Technology. Computational and Systems Biology Program. Computational and Systems Biology Program. Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2018. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references. High-throughput "omics" data are becoming commonplace in biological research and can provide important translational insights, but there is a need for well-crafted user-friendly tools for integrating and analyzing these data. In this thesis, I present versions 1 and 2 of Omics Integrator, a software tool designed to take advantage of the Prize-Collecting Steiner Forest algorithm from graph theory to provide users with high-confidence biological networks informed by their omics results. I show the results of using this flexible tool in several studies of Huntington's disease (HD), a fatal neurodegenerative disorder with no cure. By leveraging Omics Integrator on omics datasets from induced pluripotent stem cell (iPSC) derived models of HD, I discovered and highlighted several pathways that are altered in these cell line models, including neurodevelopment and glycolytic metabolism, which may lead to important therapeutic targets in the disease. Finally, I compare omics data derived from three iPSC-derived models differentiated towards a striatal neuron cell type using different protocols, and show that by performing this large comparative analysis I can implicate functions and pathways common to several models of HD. Future integrative and comparative studies like these will be made easier by the Omics Integrator tool. by Amanda Joy Kedaigle. Ph. D. 2018-11-15T15:51:34Z 2018-11-15T15:51:34Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119026 1057726996 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 315 pages application/pdf Massachusetts Institute of Technology
spellingShingle Computational and Systems Biology Program.
Kedaigle, Amanda Joy
Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title_full Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title_fullStr Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title_full_unstemmed Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title_short Integrating Omics data : a new software tool and its use in implicating therapeutic targets in Huntington's disease
title_sort integrating omics data a new software tool and its use in implicating therapeutic targets in huntington s disease
topic Computational and Systems Biology Program.
url http://hdl.handle.net/1721.1/119026
work_keys_str_mv AT kedaigleamandajoy integratingomicsdataanewsoftwaretoolanditsuseinimplicatingtherapeutictargetsinhuntingtonsdisease