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Integrative Network Approaches to Un...
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Hall, Benika Chenae.
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Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer./
作者:
Hall, Benika Chenae.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
159 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Contained By:
Dissertation Abstracts International79-05B(E).
標題:
Bioinformatics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10642074
ISBN:
9780355480887
Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
Hall, Benika Chenae.
Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 159 p.
Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2017.
Cancer is among the leading cause of deaths in men and women today. Regulation of gene expression by microRNAs (miRNA) has been linked to cancer progression in recent years. Therefore there has been a growing interest understanding how miRNAs mediate gene expression in cancer. In this dissertation we aimed to construct an integrative miRNA-gene network to understand how miRNAs affect gene expression and their downstream genetic neighborhoods in ovarian cancer and colon cancer. To conduct this research, we applied different techniques to determine how miRNAs impact downstream genetic neighborhoods and identify cancer enriched neighborhoods in ovarian and colon cancer. First, we developed a community based method utilizing the spin-glass model to construct an integrative miRNA-gene network. Second, we developed a label propagation framework to construct a multi-layer miRNA-gene network to exploit the downstream effects of miRNAs throughout integrating multiple networks. We identified multiple communities enriched in cancer-driven pathways across multiple networks in ovarian cancer. We also uncovered enriched genetic neighborhoods and identified key network signatures in patients with different pathological stages in colon cancer. The methods developed provide a better outlook on how miRNAs affect gene expression and their downstream genetic neighborhoods, which will improve our understanding of their role in tumorigenesis and cancer progression.
ISBN: 9780355480887Subjects--Topical Terms:
553671
Bioinformatics.
Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
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Cancer is among the leading cause of deaths in men and women today. Regulation of gene expression by microRNAs (miRNA) has been linked to cancer progression in recent years. Therefore there has been a growing interest understanding how miRNAs mediate gene expression in cancer. In this dissertation we aimed to construct an integrative miRNA-gene network to understand how miRNAs affect gene expression and their downstream genetic neighborhoods in ovarian cancer and colon cancer. To conduct this research, we applied different techniques to determine how miRNAs impact downstream genetic neighborhoods and identify cancer enriched neighborhoods in ovarian and colon cancer. First, we developed a community based method utilizing the spin-glass model to construct an integrative miRNA-gene network. Second, we developed a label propagation framework to construct a multi-layer miRNA-gene network to exploit the downstream effects of miRNAs throughout integrating multiple networks. We identified multiple communities enriched in cancer-driven pathways across multiple networks in ovarian cancer. We also uncovered enriched genetic neighborhoods and identified key network signatures in patients with different pathological stages in colon cancer. The methods developed provide a better outlook on how miRNAs affect gene expression and their downstream genetic neighborhoods, which will improve our understanding of their role in tumorigenesis and cancer progression.
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