Topological motif-based bio-network analysis = 위상학적 모티프 기반 바이오 네트워크 분석

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dc.contributor.advisorLee, Doheon-
dc.contributor.advisor이도헌-
dc.contributor.authorChoi, Jae-joon-
dc.contributor.author최재준-
dc.date.accessioned2018-05-23T19:33:57Z-
dc.date.available2018-05-23T19:33:57Z-
dc.date.issued2017-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=675697&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/241802-
dc.description학위논문(박사) - 한국과학기술원 : 바이오및뇌공학과, 2017.2,[v, 75 p. :]-
dc.description.abstractRecently, 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.languageeng-
dc.publisher한국과학기술원-
dc.subjecttopological motif-
dc.subjectnetwork motif-
dc.subjectbio-network analysis-
dc.subjectdrug repositioning-
dc.subjectnetwork model-
dc.subject위상학적 모티프-
dc.subject네트워크 모티프-
dc.subject바이오네트워크 분석-
dc.subject약물 재창출-
dc.subject네트워크 모델-
dc.titleTopological motif-based bio-network analysis = 위상학적 모티프 기반 바이오 네트워크 분석-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :바이오및뇌공학과,-
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