DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Doheon | - |
dc.contributor.advisor | 이도헌 | - |
dc.contributor.author | Choi, Jae-joon | - |
dc.contributor.author | 최재준 | - |
dc.date.accessioned | 2018-05-23T19:33:57Z | - |
dc.date.available | 2018-05-23T19:33:57Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=675697&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/241802 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 바이오및뇌공학과, 2017.2,[v, 75 p. :] | - |
dc.description.abstract | Recently, network motif (or graphlet) properties have been widely utilized as important topological features of bio-networks. Network motifs are recurrent and statistically significant partial subgraphs or patterns. In this thesis, we analyzed various bio-networks based on topological property of network motifs. In part I, we developed Typed Network Motif Comparison Algorithm (TNMCA) for repositioning drugs using topological properties of given networks. TNMCA is a powerful inference algorithm for multi-level biomedical interaction data as the algorithm depends on the different types of entities and relations. In part II, we propose a new network model incorporating grouped attachment (GA) and apply it to real-world networks. Corresponding networks generated by GA model showed a higher similarity of motif properties with real-world networks compared to corresponding networks generated by existing network models. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | topological motif | - |
dc.subject | network motif | - |
dc.subject | bio-network analysis | - |
dc.subject | drug repositioning | - |
dc.subject | network model | - |
dc.subject | 위상학적 모티프 | - |
dc.subject | 네트워크 모티프 | - |
dc.subject | 바이오네트워크 분석 | - |
dc.subject | 약물 재창출 | - |
dc.subject | 네트워크 모델 | - |
dc.title | Topological motif-based bio-network analysis | - |
dc.title.alternative | 위상학적 모티프 기반 바이오 네트워크 분석 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :바이오및뇌공학과, | - |
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