• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.31-40
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• 2005

In the post-genomic era, researches on proteins as well as genes have been increasingly required. Particularly, work on protein-protein interaction and protein network construction have been recently establishing. Most biologists publish their research results through papers or other media. However, biologists do not use the information effectively, because the published research results are very large. As the growth of internet field, it becomes easy to access these research results. It is important to extract information with a biological meaning from various media. Therefore, In this paper, we efficiently extract the protein information from many open papers or other media and construct the database of the extracted information. We build a protein network from the established database and then design and implement various pathway analysis algorithms which find biological meaning from the protein network.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.511-515
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• 2004

In the post-genomic era, researches on proteins as well as genes have been increasingly required. Particularly, work on protein-protein interaction and protein network construction have been recently establishing. Most biologists publish their research results through papers or other media. However, biologists do not use the information effectively, since the published research results are very large. As the growth of internet, it becomes easy to access very large research results. It is significantly important to extract information with a biological meaning from varisous media. Therefore, in this research, we efficiently extract protein-protein interaction information from many open papers or other media and construct the database of the extracted information. We build a protein network from the established database and then design and implement various pathway analysis algorithms which find biological meaning from the protein network.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.541-542
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• 2011

최근 웹 서비스 기술을 이용하여 질병이나 단백질과 같은 바이오 데이터의 분류 및 제공하는 것과 관련된 연구들이 활발하게 진행되고 있다. 웹 서비스 기반 바이오 데이터 서비스에 대한 연구는 데이터베이스의 구축을 중심으로 보고되고 있으나 이를 기반으로 한 분석 응용 도구에 대한 연구는 미미한 실정이다. 이에 따라 본 논문에서는 통합 바이오 데이터베이스를 구축하고 이를 활용한 가시화 시스템을 설계하고 구현한다. 본 시스템을 이용하여 특정 질병에 관련된 단백질 정보를 신호 전달 경로 네트워크상에 가시화하여 연구자에게 직관적으로 주요 단백질에 대한 네트워크내의 위치 정보를 제공한다.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.573-584
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• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• 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.

• Korean Journal of Poultry Science
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• v.47 no.1
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• pp.9-19
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• 2020

Avian influenza (AI) viruses are highly contagious viruses that infect many bird species and are zoonotic. Ducks are resistant to the deadly and highly pathogenic avian influenza virus (HPAIV) and remain asymptomatic to the low pathogenic avian influenza virus (LPAIV). In this study, we identified common differentially expressed genes (DEGs) after a reanalysis of previous transcriptomic data for the HPAIV and LPAIV infected duck lung cells. Microarray datasets from a previous study were reanalyzed to identify common target genes from DEGs and their biological functions. A total of 731 and 439 DEGs were identified in HPAIV- and LPAIV-infected duck lung cells, respectively. Of these, 227 genes were common to cells infected with both viruses, in which 193 genes were upregulated and 34 genes were downregulated. Functional annotation of common DEGs revealed that translation related gene ontology (GO) terms were enriched, including ribosome, protein metabolism, and gene expression. REACTOME analyses also identified pathways for protein and RNA metabolism as well as for tissue repair, including collagen biosynthesis and modification, suggesting that AIVs may evade the host defense system by suppressing host translation machinery or may be suppressed before being exported to the cytosol for translation. AIV infection also increased collagen synthesis, showing that tissue lesions by virus infection may be mediated by this pathway. Further studies should focus on these genes to clarify their roles in AIV pathogenesis and their possible use in AIV therapeutics.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.1-18
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• 2022

This study aimed to investigate the association between plant protein intake and health-related quality of life (HRQoL) in Korean individuals aged 50 years or older. Using the 2016-2018 Korea National Health and Nutrition Examination Survey data, 7,956 participants (3,434 men and 4,522 women) were included in the study. HRQoL was measured using the Euro-quality of life five-dimension (EQ5D), composed of physical function, self-care, daily activities, pain/discomfort, and anxiety/depression problems. The EQ5D estimates were converted into an EQ5D index score. The association between daily intake of plant proteins and HRQoL was evaluated using regression analysis. The intake of total plant protein, legume nut seed (LNS), and fermented bean (FERMB) proteins were all positively associated with HRQoL in both men and women (p < 0.01). Of EQ5D's five dimensions, physical function and daily activities were most commonly associated with plant protein intake. Compared to LNS protein or FERMB protein intake, total plant protein intake showed a better association with HRQoL. In conclusion, a significant association was observed between plant protein intake and HRQoL. It suggests that adequate intake of plant protein might be helpful for the maintenance or improvement of HRQoL in Korean adults.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.306-311
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• 2009

We initially obtained human diseases-related proteins dataset from the OMIM and the SWISS PROT and then constructed disease-related protein-protein interaction network. The protein network contains 40 hub proteins such as CALM1, ACTB and ABL2. The protein network can be derived the map of the relationship between different disease proteins, denoted disease interaction network. We demonstrate that the associations between diseases are directly correlated to their underlying protein-protein interaction networks. From constructed the disease-protein bipartite network, we derived 38 diseasomal proteins, including APP, ABL1 and STAT1. We previously demonstrated that hub proteins in the network tend to be diseasomal proteins in the disease-related protein sub-networks. However, we found that 18% hubs are only diseasomal proteins in the whole disease network. At this point, we could not elucidate difference in the hub-diseasomal proteins tendency between sub0network and whole network. In spite of we still have unsolved problems, our results elucidate that the discovery of protein interaction networks assigned by diseases will provide insight into the underlying molecular mechanisms and biological processes in complex human disease system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.916-919
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• 2012

Bioimaging that can be imaging phenomena within cells of a molecular size have been advanced in technology. We can observe clearly DNA and proteins using a confocal microscope. Currently biological fluorescent imaging area is used essentially for diagnosis and treatment in health and clinical care field. In this paper, we developed an integration management system of analyzing fluorescence images on smart phone. It can support a user to analyse fluorescence images anytime anywhere. And our system is based on client-server configuration and has functions that can figure intensity of fluorescence images and manage many imaging data. Proposed system can be a mean of ubiquitous health because it helps a doctor diagnose by analyzing fluorescence images of emergency patients without time and space restrictions.