• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.259-271
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• 2008

We propose a protein function finding algorithm that is able to predict specific molecular function for unannotated proteins through domain analysis from protein-protein network. To do this, we first construct protein-protein interaction(PPI) network in Saccharomyces cerevisiae from MIPS databases. The PPI network(proteins; 3,637, interactions; 10,391) shows the characteristics of a scale-free network and a hierarchical network that proteins with a number of interactions occur in small and the inherent modularity of protein clusters. Protein-protein interaction databases obtained from a Y2H(Yeast Two Hybrid) screen or a composite data set include random false positives. To filter the database, we reconstruct the PPI networks based on the cellular localization. And then we analyze Hub proteins and the network structure in the reconstructed network and define structural modules from the network. We analyze protein domains from the structural modules and derive functional modules from them. From the derived functional modules with high certainty, we find tentative functions for unannotated proteins.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1602-1610
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• 2004

As various genome projects have produced enormous amount of biosequence data, functional sequence analysis in terms of tile nucleic acid and protein becomes very significant. In functional genomics and proteomics, the functional analysis of each individual gene and protein remains a big challenge. Contrary to traditional studies, which regard proteins as not components of a whole protein interaction network but individual entities, recent studies have focused on examining functions and roles of each individual gene and protein in view of a whole life system. In this regard, it has been recognized as an appropriate method to analyze protein function on the basis of synthetic information of its interaction and domain modularity. In this context, this paper introduces the PIVS (Protein-protein interaction Inference & Visualization System), which predicts the interaction relationship of input proteins by taking advantage of information on homology degree, domain modules which input sequences contain, and protein interaction relationship. The information on domain modules can increase the accuracy of the function and interaction relationship analysis in terms of the specificity and sensitivity.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.60-67
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• 2009

Analyzing protein-protein interactions(PPI) is an important task in bioinformatics as it can help in new drugs' discovery process. However, due to vast amount of PPI data and their complexity, efficient visualization of the data is still remained as a challenging problem. We have developed efficient and effective visualization system that integrates Gene Ontology(GO) and PPI network to provide better insights to scientists. To provide efficient data visualization, we have employed dynamic interactive graph drawing methods and context-based browsing strategy. In addition, quick and flexible cross-reference system between GO and PPI; LCA(Least Common Ancestor) finding for GO; and etc are supported as special features. In terms of interface, our visualization system provides two separate graphical windows side-by-side for GO graphs and PPI network, and also provides cross-reference functions between them.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.579-582
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• 2010

본 논문은 기존의 상호 작용 UCC 제작에서 한 단계 더 나아가 상호작용 UCC를 스마트폰에 적용하는 방법을 연구하는 논문입니다. 상호작용 UCC라 함은 기존의 일반 UCC에서 벗어나 사용자의 조작과 체험이 가능하도록 제작한 UCC를 말하는데 이러한 상호작용 UCC를 스마트폰에 적용해보려고 합니다. 최근 스마트폰은 전 세계인의 주목을 받고 있습니다. 기존 핸드폰의 전화기능에서부터 시작하여 음악, 동영상 재생 등 기능을 비롯하여 웹서핑, 지도 등 다양한 기능을 통해 우리들에게 편리함을 안겨주고 있습니다. 하지만 사용자들과 함께 상호작용을 고려한 상호작용 UCC와 스마트폰과 관련되어진 연구는 거의 존재하지 않습니다. 상호작용 UCC의 장점과 스마트폰의 기능을 융합한다면 훌륭한 효과를 낼 수 있다고 생각합니다. 본 연구팀에서 제작하려는 스마트폰 기반의 상호작용 UCC는 사용자들과 함께 의사소통 하고, 제공자 기반에서 존재하는 UCC의 결함을 해결하기 위해 실증적인 요소가 가미된 새로운 형태의 UCC입니다. 이를 통해 제작자가 자신이 전달하고자 하는 바를 보다 더 효과적으로 전달할 수 있도록 하는 방법을 제시하려 합니다.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.81-99
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• 2021

The purpose of this study was to examine the effect of parent-child interactions on children's academic performance focusing on the mediating effect of children's executive function difficulty. The data for this study were drawn from the Panel Study on Korean Children(PSKC). The participants were 559 children of elementary school and their families from 8th wave(1^st graders), 9th wave(2^nd graders), and 10th wave(3^rd graders) of PSKC. The data were analyzed with structural equation modeling. The results of this study were as follows. First, mother-child interaction and father-child interaction didn't have a significant direct effect on children's academic performance. Second, mother-child interaction had a significant positive indirect influences on academic performance through children's executive function difficulty. The results of this study indicated that mother-child interaction and children's executive function difficulty are important for children's academic performance.

• Journal of Life Science
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• v.14 no.6 s.67
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• pp.997-1002
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• 2004

This paper deals with the WASPIFA (Web-based Assistant System for Protein-protein Interaction and Function Analysis) system that can provide the comprehensive information on Protein-protein interaction and function concerned with function analysis. Different from existing systems for protein function and protein-protein interaction analysis, which provide fragmentary information restricted to specific field, our system furnishes end-user with comprehensive and synthetic information on the input sequence to be analyzed, including function and annotation information, domain information, and interaction relationship information. The synthetic information that our system contains as local databases has been extracted from many resources related to function, annotation, motif and domain by various pre-processing. Employing our system, end-users can evaluate and judge the synthetic results to do protein interaction and function analysis effectively. In addition, the WASPIFA system is equipped with automatic system management and data update function that facilitates system manager to maintain and manage it efficiently.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.101-108
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• 2019

Family tourism has become the mainstream demand of the tourism market, and it is also an effective way to obtain happiness. This paper takes family tourists as the research object, takes the family tourism family affection interaction behavior and the experience value relationship as the link, Empirically tests the family tourism "interaction behavior-social support-experience value" conceptual model and the relationship hypothesis. The results showed that interaction of family affection had a positive and significant effect on the functional, cognitive and emotional experience value of family tourists. Family interaction in family tourism has a significant positive impact on social support. Social support has significant positive effects on functional, cognitive, emotional and overall experiential values. This conclusion expands the theoretical and empirical research on the relationship between interaction behavior and experience value, and provides a basis for understanding the interaction behavior and experience value of family love from the perspective of tourism experience essence.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.238-240
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• 2005

단백체는 세포가 처해있는 환경에 따라, 그리고 각 조직 별로 유동적으로 존재하며, 세포의 실제적인 기능을 표현해준다. 이러한 이유로 세포 내에서 일어나는 실제적인 현상들을 전체 단백질 단계에서 통합적으로 파악하고자 하는 단백체학 연구가 활발하게 진행되고 있다. 미지의 단백질의 기능을 밝혀내는 연구는 단백체학의 가장 기본적이면서 중요한 부분이라고 할 수 있다. 본 논문에서는 "단백질 상호작용 네트웍 사전(PIND)"을 구축함으로써 단백질의 기능을 예측하는 새로운 방법론을 소개한다.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.209-214
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• 2005

The use of protein interaction data is highly reliable for predicting functions to proteins without function in proteomics study. The computational studies on protein function prediction are mostly based on the concept of guilt-by-association and utilize large-scale interaction map from revealed protein-protein interaction data. This study compares graph-based approaches such as neighbor-counting and $\chi^2-statistics$ methods using protein-protein interaction data and proposes an approach that is effective in analyzing large-scale protein interaction data. The proposed approach is also based protein interaction map but sequence similarity and heuristic knowledge to make prediction results more reliable. The test result of the proposed approach is given for KDD Cup 2001 competition data along with those of neighbor-counting and $\chi^2-statistics$ methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.172-175
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• 2012

스마트 컴퓨팅은 지능형 정보서비스로서 스마트폰, 스마트패드, 스마트TV 등의 다양한 스마트 기기를 비롯한 스마트 워크, 스마트 자동차 등의 새로운 정보화시스템 개념으로 대두되고 있다. 본 논문은 스마트 컴퓨팅의 컴퓨팅 환경과 최적의 정보 상호작용을 정립하기 위해서 정보 상호작용에 대한 상황 인식 기반 구조적, 기능적, 인터페이스 접근에 대해서 논의한다. 이러한 정보 상호작용을 통해서 사용자 컴퓨팅 환경에 최적화된 스마트 정보시스템의 효율적 구성과 사용자 정보서비스의 편의성을 구축한다.