Analysis of regulatory motifs in cellular signaling network for human diseases세포 신호 전달 네트워크에서 질병에 대한 조절 모티프 특징 해석에 대한 연구

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The cell is continually processing intracellular information and making decisions to make appropriate responses through various intracellular regulations such as gene expression, metabolic activity, movement, growth and division. The information-processing abilities of a cell are carried out by complex signaling networks of interacting genes and proteins. Understanding how the information of a cell is processed is one of the major challenges in biological research. Recently, it is known that complex signaling network includes various types of regulatory circuits which are patterns of activation and inhibition and these regulatory circuits have significantly crucial roles in regulating specific dynamic behaviors. For the purpose of identifying these regulatory circuits in cellular signaling network in the field of computational systems biology, network motif finding is widely used for identifying various regulatory motifs, which are conserved regulatory circuits. However, the network structures of the regulatory motifs are highly diverse and complex so that previous study was limitedly performed for two- or three-node regulatory motifs or specific network patterns such as feedback loop or feed-forward loop. In order to overcome these limitations, we need to employ the novel computational method to detect the various forms of network structure of regulatory motifs in signaling network. In addition, we must consider the largest signaling network for comprehensive regulatory motif analysis. In this thesis, we have performed the comprehensive computational analysis of human cellular signaling network by employing novel computational approaches to extensively identify various forms of network structures of regulatory motifs for characterizing the properties of regulatory motifs. Our novel computational method supports identification of both regulatory circuit and regulatory motifs in cellular signaling network for efficient regulatory motif analysis. Regulatory...
Yi, Gwan-Suresearcher이관수
한국과학기술원 : 정보통신공학과,
Issue Date
566049/325007  / 020058007

학위논문(박사) - 한국과학기술원 : 정보통신공학과, 2013.8, [ viii, 98 p. ]


Computational systems biology; 인간 질병; 세포 시그널링 네트워크; 조절 회로; 조절 모티프; 계산 시스템스 생물학; Regulatory motif; Regulatory circuit; Cellular signaling network; Human disease

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