Identification of domain pattern in human proteins using association rules = 어소시에이션 룰 학습을 이용한 인간 단백질의 도메인 패턴 추출

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dc.contributor.advisorHan, Dong-Soo-
dc.contributor.authorJung, Suk-Hoon-
dc.description학위논문(석사) - 한국정보통신대학교 : 공학부, 2007.2, [ vi, 71 p. ]-
dc.description.abstractIn this paper, we introduce a formulated method to evaluate significance of each domain combination, which exploits association rules, and report an overview of domain combination by identifying domain pattern and analyzing their functional annotations. As proteins have evolved toward specific functions, domains, fundamental functional units, have high tendency to form patterns. Domain patterns must be significant domain combinations that have biological reasons to be assembled. Introduced method measures co-occurrence frequency and mutual dependency of domains in a domain combination, so it is useful to estimate whether a given domain combination is meaningful or not. Also we devised functional cohesiveness measure, which makes use of GO term annotation of domains, to investigate biological meaning of domain patterns. Based on the methods, we extracted domain patterns in human proteins and investigated functional annotations of them. From the results, we drew conclusionS that domains in human proteins form patterns whose members are highly affiliated to one another, and that extracted patterns tend to be associated with molecular function and biological process.eng
dc.subjectDomain Combination-
dc.subjectDomain Pattern-
dc.subjectProtein domain-
dc.subjectAssociation Rules-
dc.subject어소시에이션 룰-
dc.subject도메인 조합-
dc.subject도메인 패턴-
dc.subject단백질의 도메인-
dc.titleIdentification of domain pattern in human proteins using association rules = 어소시에이션 룰 학습을 이용한 인간 단백질의 도메인 패턴 추출-
dc.description.department한국정보통신대학교 : 공학부, -
dc.contributor.localauthorHan, Dong-Soo-
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School of Engineering-Theses_Master(공학부 석사논문)
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