• Title/Summary/Keyword: tagging system

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Spectrofluorometric Characteristics of the N-Terminal Domain of Riboflavin Synthase (아미노-말단 리보플라빈 생성효소 단백질의 형광 특성)

  • Kim, Ryu-Ryun;Yi, Jeong-Hwan;Nam, Ki-Seok;Ko, Kyung-Won;Lee, Chan-Yong
    • Korean Journal of Microbiology
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    • v.47 no.1
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    • pp.14-21
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    • 2011
  • Riboflavin synthase catalyzes the formation of one molecule of each riboflavin and 5-amino-6-ribitylamino-2,4-pyrimidinedione by the transfer of a 4-carbon moiety between two molecules of the substrates, 6,7-dimetyl-8-ribityllumazine. The most remarkable feature is the sequence similarity between the N-terminal half (1-97) and the C-terminal half domain (99-213). To investigate the structure and fluorescent characteristics of the N-terminal half of riboflavin synthase (N-RS) in Escherichia coli, more than 10 mutant genes coding for the mutated N-terminal domain of riboflavin synthase were generated by polymerase chain reaction. The genes coding for the proteins were inserted into pQE vector designed for easy purification of protein by 6X-His tagging system, expressed, and the proteins were purified. Almost all mutated N-terminal domain of riboflavin synthases bind to 6,7-dimethyl-8-ribityllumazine and riboflavin as fluorescent ligands. However, N-RS C47D and N-RS ET66,67DQ mutant proteins show colorless, indicating that fluorescent ligands were dissociated during purification. In addition, most mutated proteins show low fluorescent intensity comparing to N-RS wild type, whereas N-RS C48S posses stronger fluorescent intensity than that of wild type protein. Based on this result, N-RS C48S can be used as the tool for high throughput screening system for searching for the compound with inhibitory effect for the riboflavin synthase.

The Expression Patterns of Human Parkin in E. codi and Mammalian Cells (대장균과 포유류 세포 내에서 parkin의 발현 양상에 관한 연구)

  • Nam Min-Kyung;Park Hye-Min;Choi Ju-Youn;Park Hyo-Jin;Chung Kwang Chul;Kang Seong man;Rhim Hyangshuk
    • Journal of Life Science
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    • v.15 no.6 s.73
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    • pp.916-922
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    • 2005
  • Parkin, known as an E3 ubiquitin ligase, has essential role in protein quality control, and its severe dysfunction leads to neurodegenerative disorders. Human Parkin was excessively degraded when expressed in Escherichia coli under the conventional induction condition ($37^{\circ}C$ culture condition with 0.5 mM IPTG). To optimize the induction and culture conditions for recombinant human Parkin and develop a rapid method for the Parkin purification, we expressed Parkin by using PCEX system at the different culture temperatures and IPTC concentrations. The intact Parkin protein was purified to approximately $90\%$ purity with suitable amounts of protein under the optimal culture condition ($25^{\circ}C$E with 0.01 mM IPTG). Additionally, we constructed various parkin plasmids with different tagging systems and investigated their expression patterns in HEK293 cells. We found that the proteolytically sensitive site is localized within a ubiquitin-like domain of Parkin. This study developes a method for generating useful reagents to investigate biochemical properties of Parkin.

Flavonoid Biosynthesis: Biochemistry and Metabolic Engineering (Flavonoid 생합성:생화학과 대사공학적 응용)

  • Park, Jong-Sug;Kim, Jong-Bum;Kim, Kyung-Hwan;Ha, Sun-Hwa;Han, Bum-Soo;Kim, Yong-Hwan
    • Journal of Plant Biotechnology
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    • v.29 no.4
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    • pp.265-275
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    • 2002
  • Flavonoid biosynthesis is one of the most extensively studied areas in the secondary metabolism. Due to the study of flavonoid metabolism in diverse plant system, the pathways become the best characterized secondary metabolites and can be excellent targets for metabolic engineering. These flavonoid-derived secondary metabolites have been considerably divergent functional roles: floral pigment, anticancer, antiviral, antitoxin, and hepatoprotective. Three species have been significant for elucidating the flavonoid metabolism and isolating the genes controlling the flavonoid genes: maize (Zea mays), snapdragon (Antirrhinum majus) and petunia (Prtunia hybrida). Recently, many genes involved in biosynthesis of flavonoid have been isolated and characterized using mutation and recombinant DNA technologies including transposon tagging and T-DNA tagging which are novel approaches for the discovery of uncharacterized genes. Metabolic engineering of flavonoid biosynthesis was approached by sense or antisense manipulation of the genes related with flavonoid pathway, or by modified expression of regulatory genes. So, the use of a variety of experimental tools and metabolic engineering facilitated the characterization of the flavonoid metabolism. Here we review recent progresses in flavonoid metabolism: confirmation of genes, metabolic engineering, and applications in the industrial use.

Construction, Expression, and Purification of N-Terminal Variants of Lumazine Protein from Photobacterium leiognathi (발광세균 Photobacterium leiognathi의 돌연변이 아미노-말단 루마진 단백질들의 제조, 발현 및 정제)

  • Kang, Kyoung-Suk;Kim, So-Young;Choi, Ji-Sun;Kim, Young-Doo;Pokoo, Robert;Nam, Ki-Seok;Lee, Chan Yong
    • Korean Journal of Microbiology
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    • v.49 no.2
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    • pp.205-210
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    • 2013
  • Lumazine protein is a fluorescent protein isolated from the bioluminescent bacteria of Photobacterium species. To generate minimal size of lumazine protein with possessing fluorescent characteristic, the gene coding for the wild type N-terminal domain of lumazine protein (N-LumP 118) containing amino acids up to 118 from Photobacterium leiognathi was produced. In addition, the genes coding for the variant proteins of N-LumP 118, replaced with one tryptophan amino acid (N-LumP 118 V41W, S48W, T50W, D64W, and A66W), were also constructed by Polymerase Chain Reaction and Site Directed Mutagenesis. These proteins were expressed in Escherichia coli by transformation with recombinant plasmids and purified by 6X-His tagging system. Spectroscopic studies have show that the purified proteins are capable of binding to the fluorescent ligand 6,7-dimethyl-8-ribityllumazine, resulted in showing of fluorescent characteristic with the minimal size of protein. From these studies, the mutant proteins containing single tryptophan amino acid residue, possessing its own intrinsic flouophore character at the different position, will be able to the use as a probe for further studies to deduce their three dimensional structure and the binding modes.

Dual-band RFID Tag Antenna Applicable for RF Power Harvester System (RF 에너지 충전 시스템 기능을 위한 이중대역 RFID 태그 안테나)

  • Mun, Byeonggwi;Rhee, Changyong;Kim, Jae-Sik;Cha, Junghoon;Lee, Byungje
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.5
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    • pp.46-51
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    • 2013
  • In this paper, a dual-band antenna is proposed for the RF power harvester system as well as RFID tag. The proposed antenna operates as the passive and active RFID tag antenna in the UHF and microwave band, respectively. In addition, to charge the battery of an active RFID tag in the microwave band, it harvest the RF signal for tagging from the passive RFID tag antenna in the UHF band. The proposed antenna operates in the UHF band (917~923.5 MHz) and microwave band (2.4~2.45 GHz). In order to obtain the dual-band operation, the dipole structure and meander parasitic elements are proposed as the ${\lambda}/2$ and $1{\lambda}$ dipole antenna, respectively. The radiating dipole structure in the microwave band acts as the coupled feed for the meander parasitic elements in the UHF band. The impedance bandwidth (VSWR < 2) of the proposed antenna covers 917~923.5 MHz (UHF band) and 2.4~2.45 GHz (Microwave band). Measured total efficiencies are over 45 % in the UHF band and over 70 % in the microwave band. Peak gains are over 0.18 dBi and 2.8 dBi in the UHF and microwave band with an omni-directional radiation pattern, respectively.

Construction of Test Collection for Automatically Extracting Technological Knowledge (기술 지식 자동 추출을 위한 테스트 컬렉션 구축)

  • Shin, Sung-Ho;Choi, Yun-Soo;Song, Sa-Kwang;Choi, Sung-Pil;Jung, Han-Min
    • The Journal of the Korea Contents Association
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    • v.12 no.7
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    • pp.463-472
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    • 2012
  • For last decade, the amount of information has been increased rapidly because of the internet and computing technology development, mobile devices and sensors, and social networks like facebook or twitter. People who want to gain important knowledge from database have been frustrated with large database. Many studies for automatic knowledge extracting meaningful knowledge from large database have been fulfilled. In that sense, automatic knowledge extracting with computing technology has been highly significant in information technology field, but still has many challenges to go further. In order to improve the effectives and efficiency of knowledge extracting system, test collection is strongly necessary. In this research, we introduce a test collection for automatic knwoledge extracting. We name the test collection KEEC/KREC(KISTI Entity Extraction Collection/KISTI Relation Extraction Collection) and present the process and guideline for building as well as the features of. The main feature is to tag by experts to guarantee the quality of collection. The experts read documents and tag entities and relation between entities with a tool for tagging. KEEC/KREC is being used for a research to evaluate system performance and will continue to contribute to next researches.

Development of Dynamic Passenger-Trip Assignment Model of Urban Railway Using Seoul-Incheon-Gyeonggi's Transportation Card (대중교통카드기반 수도권 도시철도 통행수요배정모형)

  • Sohn, Jhieon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.1
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    • pp.105-114
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    • 2016
  • With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.

COVID-19-related Korean Fake News Detection Using Occurrence Frequencies of Parts of Speech (품사별 출현 빈도를 활용한 코로나19 관련 한국어 가짜뉴스 탐지)

  • Jihyeok Kim;Hyunchul Ahn
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.267-283
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    • 2023
  • The COVID-19 pandemic, which began in December 2019 and continues to this day, has left the public needing information to help them cope with the pandemic. However, COVID-19-related fake news on social media seriously threatens the public's health. In particular, if fake news related to COVID-19 is massively spread with similar content, the time required for verification to determine whether it is genuine or fake will be prolonged, posing a severe threat to our society. In response, academics have been actively researching intelligent models that can quickly detect COVID-19-related fake news. Still, the data used in most of the existing studies are in English, and studies on Korean fake news detection are scarce. In this study, we collect data on COVID-19-related fake news written in Korean that is spread on social media and propose an intelligent fake news detection model using it. The proposed model utilizes the frequency information of parts of speech, one of the linguistic characteristics, to improve the prediction performance of the fake news detection model based on Doc2Vec, a document embedding technique mainly used in prior studies. The empirical analysis shows that the proposed model can more accurately identify Korean COVID-19-related fake news by increasing the recall and F1 score compared to the comparison model.

The Individual Discrimination Location Tracking Technology for Multimodal Interaction at the Exhibition (전시 공간에서 다중 인터랙션을 위한 개인식별 위치 측위 기술 연구)

  • Jung, Hyun-Chul;Kim, Nam-Jin;Choi, Lee-Kwon
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.19-28
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    • 2012
  • After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

Development of Information Extraction System from Multi Source Unstructured Documents for Knowledge Base Expansion (지식베이스 확장을 위한 멀티소스 비정형 문서에서의 정보 추출 시스템의 개발)

  • Choi, Hyunseung;Kim, Mintae;Kim, Wooju;Shin, Dongwook;Lee, Yong Hun
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.111-136
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    • 2018
  • In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.