abstract: Given the process of tumorigenesis, biological signaling pathways have become of interest in the field of oncology. Many of the regulatory mechanisms that are altered in cancer are directly related to signal transduction and cellular communication. Thus, identifying signaling pathways that have become deregulated may provide useful information to better understanding altered regulatory mechanisms within cancer. Many methods that have been created to measure the distinct activity of signaling pathways have relied strictly upon transcription profiles. With advancements in comparative genomic hybridization techniques, copy number data has become extremely useful in providing valuable information pertaining to the genomic landscape of cancer. The purpose of this thesis is to develop a methodology that incorporates both gene expression and copy number data to identify signaling pathways that have become deregulated in cancer. The central idea is that copy number data may significantly assist in identifying signaling pathway deregulation by justifying the aberrant activity being measured in gene expression profiles. This method was then applied to four different subtypes of breast cancer resulting in the identification of signaling pathways associated with distinct functionalities for each of the breast cancer subtypes. / Dissertation/Thesis / M.S. Computer Science 2011
| Identifer | oai:union.ndltd.org:asu.edu/item:9422 |
| Date | January 2011 |
| Contributors | Trevino, Robert (Author), Kim, Seungchan (Advisor), Ringner, Markus (Committee member), Liu, Huan (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 68 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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