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Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer./
Author:	Hall, Benika Chenae.
Description:	1 online resource (159 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Contained By:	Dissertation Abstracts International79-05B(E).
Subject:	Bioinformatics. -
Online resource:	click for full text (PQDT)
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. - 1 online resource (159 pages)

Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355480887Subjects--Topical Terms:

583857
Bioinformatics.
Index Terms--Genre/Form:

554714
Electronic books.

Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
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245 1 0 $a Integrative Network Approaches to Understanding MicroRNA and Gene Expressions in Cancer.
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500 $a Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
500 $a Adviser: Xinghua Shi.
502 $a Thesis (Ph.D.) $c The University of North Carolina at Charlotte $d 2017.
504 $a Includes bibliographical references
520 $a 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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Bioinformatics. $3 583857
650 4 $a Computer science. $3 573171
650 4 $a Health sciences. $3 1179212
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710 2 $a The University of North Carolina at Charlotte. $b Bioinformatics. $3 1182806
773 0 $t Dissertation Abstracts International $g 79-05B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10642074 $z click for full text (PQDT)