Identification of heterogeneous cancer mechanisms by using modular gene expression patterns = 모듈화된 유전자 발현 패턴을 이용한 암의 이질성 기전 발굴

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Cancer is known for its heterogeneous clinical behaviors and various patient outcomes. For the understanding of the complexities of the disease mechanisms and to develop more efficient therapeutic strategies, the ability to dissect this heterogeneity and to identify subgroups representing the common cancer mechanisms is crucial. In this study, we used an integrative transcriptome analysis to identify transcriptional modules as functional base of breast cancer mechanisms. We identified gene modules that shared co-expressed patterns in a subset of patients across multiple datasets. The composite functions of gene modules were inferred. We show that the identified subgroups share patterns of module activity and exhibit clinical and biological properties. Our results showed molecular bases of breast cancer for improved predictor and classifier in clinical use.
Advisors
Yi, GwanSuresearcher이관수researcher
Description
한국과학기술원 :바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2017
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 바이오및뇌공학과, 2017.8,[v, 87 p. :]

Keywords

암 이질성▼a환자 부분군▼a유전자 모듈▼a임상적 예후▼a바이클러스터링; cancer heterogeneous▼apatient subgroup▼agene module▼aclinical outcome▼abiclustering

URI
http://hdl.handle.net/10203/241815
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718964&flag=dissertation
Appears in Collection
BiS-Theses_Ph.D.(박사논문)
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