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Essentiality of Hub Proteins in Protein-protein Interaction Networks of Yeast
Jea Woon Ryu,이윤경,강태호,유재수,정진수,박별나,김학용,여명호 한국물리학회 2010 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.56 No.5
Scale-free protein interaction networks contain a small number of highly connected proteins, called hubs, and a large number of poorly connected proteins. Recently, several independent studies have elucidated that hub proteins are more likely to be essential to cell function than non-hub proteins. Deletion of a hub protein is more likely to be lethal than deletion of a non-hub protein. This concept defines the centrality-lethality rule; it indicates the importance of hub proteins in a complex protein network and the significance of the network architecture. Determination of the link number for a hub protein is obscure. Therefore, it is important to decide how many link numbers the hub proteins have. Here, we propose a new approach for determining the link number of hub proteins. Hub links were counted by locating the intersection point between the power-law distributions of essential and non-essential proteins. Application of this method to the Uetz database yielded an estimate of seven for the minimum number of hub protein links in yeast. Other public database (Ito, DIP,SGD, and BioGRID) predicted a different number of hub protein links. To assess the reliability of the centrality-lethality rule, we examined the essentiality of hub proteins in the protein interaction networks defined within each of the five public datasets: Uetz, Ito, DIP, SGD, and BioGRID. All five sites indicated that hub proteins were more likely to be essential than were non-hub proteins. This new method for determining the number of hub links is a useful tool for hub proteins.
Jea Woon Ryu,김학용,유재수,정진수,Tae Ho Kang 한국물리학회 2007 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.51 No.5
We have constructed and analyzed a protein-protein interaction network from the \textit{Saccharomyces cerevisiae} genome by using public genomic sequences. This provides a starting point for the construction of protein network analysis, leading to a better understanding of the functions of uncharacterized proteins and of the cellular functions of modules the networks. We acquired a highly filtered reliable protein interaction database through filtering by using subcellular localization and by using protein domains. The protein-protein interaction network constructed from the highly filtered protein interaction database shows scale-free and hierarchical properties as most networks in complex systems. For the prediction of unannotated proteins, we employed a modified Chi-square method based on neighborhood counting within structural modules and we predicted and elucidated the functions of the 98 unannotated proteins with high certainty.
네트워크 기반 코로나바이러스감염증-19 이후 세계화 분석
유제운(Jea Woon Ryu),김학용(Hak Yong Kim) 한국콘텐츠학회 2021 한국콘텐츠학회논문지 Vol.21 No.6
2020년은 코로나바이러스감염증-19(코로나19)가 세계적 대유행인 팬데믹(pandemic)으로 인해 전 세계가 혼돈 속에서 보낸 한 해였다. 14세기 중세 유럽의 봉건제도를 무너뜨린 흑사병(페스트), 17세기 스페인에 의해 잉카제국의 멸망을 이끈 천연두, 제1차 세계대전을 조기 종식시킨 스페인독감처럼 팬데믹은 역사 전환의 기점에 있었다. 코로나 19이후 다가올 대변환을 다양한 분야와 관점에서 제시하고 있으나 전환에 대한 이해와 방향이 모호한 측면이 있다. 본 연구에서는 코로나19 이후 ‘세계가 어떻게 변할 것인가’, 다시 말해 세계화에 대한 미래를 네트워크 기반으로 핵심용어를 도출하여 분석하고자 하였다. 세계화, 반세계화, 코로나19 이후 세계화와 디지털화에 관한 네트워크 및 4종류를 통합한 네트워크를 구축하였다. 네트워크로부터 허브 용어, 응집중심성 용어, K-코어 알고리즘을 적용한 단순화 네트워크로 부터 핵심용어를 추출하여 코로나19 이후 세계화의 변화를 분석하였다. 본 연구는 코로나 이후 사회적 변화를 이해하는데 있어서 네트워크를 기반으로 핵심용어를 도출하고 분석하는 방법을 제시한 것이 의미가 있을 것으로 사료된다. 2020 was a year in which the world spent in disorder due to the pandemic of Coronavirus infection-19(COVID-19). The pandemic was at the beginning of a turning point in history. For examples, the Black Death(Pest) that destroyed the feudal system of medieval Europe in the 14th century, smallpox that led to the destruction of the Inca Empire by Spain in the 17th century, and the Spanish flu that ended World War I early. The great transformation that will come after COVID-19 is presented from various fields and perspectives, but the understanding and direction of the transformation is ambiguous. This study attempts to derive and to analyze core terms based on a network of the future of globalization after COVID-19. Four Networks related to globalization, anti-globalization, and globalization and digitalization after COVID-19 were established respectively. A network integrating four networks was also constructed. The core terms were extracted from the hub nodes, the stress centrality, and the simplified network to which the K-core algorithm was applied. After COVID-19, the changes in globalization were analyzed from the extracted core terms. This study is thought to be meaningful to propose a method of deriving and analyzing core terms based on a network in understanding social changes after COVID-19.
한국영화 100선에 등장하는 영화배우 네트워크 확장 패턴 분석
류제운(Jea Woon Ryu),김학용(Hak Yong Kim) 한국콘텐츠학회 2010 한국콘텐츠학회논문지 Vol.10 No.7
복잡계 과학의 발달에 따라 많은 사회 네트워크들이 분석되어 지고 있다. 우리는 사회 네트워크의 하나로 한국영화 100선을 중심으로 한국 영화배우 네트워크를 구축하고 분석하였다. 현재까지 연결선수, 중간성(betweenness), 결집계수 등 링크수를 중심으로 네트워크의 구조를 분석하는 방향으로 진행되어지고 있다. 하지만 이제는 네트워크의 구조적 분석에서 멈추는 것이 아니라, 나아가 k-core 분석법 등을 이용하여 복잡한 네트워크 속에서 핵심 되는 중심 모듈을 찾아 분석하는 정보 분석 방향으로 진행되어야 할 것이다. 본 논문은 한국 영화 데이터베이스에서 제공하는 한국영화 100선에 출연하는 영화배우 네트워크를 만들어 가중치 유무에 따른 핵심 모듈 분석과 네트워크가 시기별로 확장되어 가는 양상을 분석하였다. 이는 네트워크의 확장 또는 진화를 이해하는 모델을 위한 기초 자료로 활용될 것으로 기대한다. The advancement of the Science for complex systems enables the analysis of many social networks. We constructed and analyzed a Korean movie star network as one of social networks, based on the 100 Korean movie selection for a main data source. Until now, the research trend has been the structural analysis of network, focused on link numbers, such as degree, betweenness and clustering coefficient. But it is time that the research is not limited by the structural analysis of networks only. Rather, the research goal should be aimed to an information analysis, performed by identifying and analyzing central modules that are regarded as the core of complex networks, using k-core analysis method. In this research, we constructed a network of movie stars who have appeared in 100 Korean movie selection, provided by Korean movie database, also we analyzed its core modules with and without weights, and the trend of seasonal expansion of the network. We expect our findings can be used as the basic data applicable to a model for understanding of the expansion and evolution of networks.