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Multi-omics data is difficult to interpret due to the heterogeneity of information by the volume of data, the complexity of characteristics of each data, and the diversity of omics platforms. There is not yet a system for interpreting to visualize research data on environmental diseases concerning environmental harmful substances. We provide MEE, a web-based visualization tool, to comprehensively explore the complexity of data due to the interconnected characteristics of high-dimensional data sets according to exposure to various environmental harmful substances. MEE visualizes omics data of correlation between omics data, subjects and samples by keyword searches of meta data, multi-omics data, and harmful substances. MEE has been demonstrated the versatility by two examples. We confirmed the correlation between smoking and asthma with RNA-seq and Methylation-Chip data, it was visualized that genes (PHACTR3, PXDN, QZMB, SOCS3 etc.) significantly related to autoimmune or inflammatory diseases. To visualize the correlation between atopic dermatitis and heavy metals, we selected 32 genes related immune response by integrated analysis of multi-omics data. However, it did not show a significant correlation between mercury in blood and atopic dermatitis. In the future, should continuously collect an appropriate level of multi-omics data in MEE system, will obtain data to analyze environmental substances and diseases.

Multi-omics data is difficult to interpret due to the heterogeneity of information by the volume of data, the complexity of characteristics of each data, and the diversity of omics platforms. There is not yet a system for interpreting to visualize research data on environmental diseases concerning environmental harmful substances. We provide MEE, a web-based visualization tool, to comprehensively explore the complexity of data due to the interconnected characteristics of high-dimensional data sets according to exposure to various environmental harmful substances. MEE visualizes omics data of correlation between omics data, subjects and samples by keyword searches of meta data, multi-omics data, and harmful substances. MEE has been demonstrated the versatility by two examples. We confirmed the correlation between smoking and asthma with RNA-seq and Methylation-Chip data, it was visualized that genes (PHACTR3, PXDN, QZMB, SOCS3 etc.) significantly related to autoimmune or inflammatory diseases. To visualize the correlation between atopic dermatitis and heavy metals, we selected 32 genes related immune response by integrated analysis of multi-omics data. However, it did not show a significant correlation between mercury in blood and atopic dermatitis. In the future, should continuously collect an appropriate level of multi-omics data in MEE system, will obtain data to analyze environmental substances and diseases.

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기사명 저자명 페이지 원문 목차
심층 강화학습을 이용한 디지털트윈 및 시각적 객체 추적 = Digital twin and visual object tracking using deep reinforcement learning 박진혁, Khurshedjon Farkhodov, 최필주, 이석환, 권기룡 p. 146-156
장단기 앙상블 모델과 이미지를 활용한 주가예측 향상 알고리즘 : Stock price prediction improvement algorithm using long-short term ensemble and chart images : focusing on the petrochemical industry / 석유화학기업을 중심으로 방은지, 변희용, 조재민 p. 157-165
차내 경험의 디지털 트랜스포메이션과 오디오 기반 인터페이스의 동향 및 시사점 = Trends and implications of digital transformation in vehicle experience and audio user interface 김기현, 권성근 p. 166-175
텍스처 특징 기반 제어점 선택 알고리즘과 병렬 심층 컨볼루션 신경망을 이용한 새로운 얼굴 모핑 방법 = A new face morphing method using texture feature-based control point selection algorithm and parallel deep convolutional neural network 박진혁, Rafiul Hasan Khan, 임선자, 이석환, 권기룡 p. 176-188
LNG 저장탱크용 작업안전 환경 센싱 모듈의 특성 연구 = A study on the characteristics of the work safety environment sensing module for LNG storage tanks 박병진, 김민성 p. 189-196
Production equipment monitoring system based on cloud computing for machine manufacturing tools Sungun Kim, Heung-Sik Yu p. 197-205
아리랑 5호 위성 영상에서 수계의 의미론적 분할을 위한 딥러닝 모델의 비교 연구 = Comparative study of deep learning model for semantic segmentation of water system in SAR images of KOMPSAT-5 김민지, 김승규, 이도훈, 감진규 p. 206-214
얼굴 감정을 이용한 시청자 감정 패턴 분석 및 흥미도 예측 연구 = A study on sentiment pattern analysis of video viewers and predicting interest in video using facial emotion recognition 조인구, 공연우, 전소이, 조서영, 이도훈 p. 215-220
BLE 네트워크에서 무결성 침해 중간자 공격에 대한 대응기법 = Countermeasure against MITM attack integrity violation in a BLE network 한혜경, 이병문 p. 221-236
무인비행기의 항행 데이터 분석을 통한 최적화된 프로파일 설계 및 구현 = Design and implementation of optimized profile through analysis of navigation data analysis of unmanned aerial vehicle 이원진 p. 237-246
Siame-FPN기반 객체 특징 추적 알고리즘 = Object feature tracking algorithm based on siame-FPN 김종찬, 임수창 p. 247-256
머신러닝기반의 데이터 결측 구간의 자동 보정 및 분석 예측 모델에 대한 연구 = A novel on auto imputation and analysis prediction model of data missing scope based on machine learning 정세훈, 이한성, 김준영, 심춘보 p. 257-268
텍스트마이닝 방법을 이용한 간편결제서비스 이용자의 질문 분석 = Research on the users' inquiries on the easy payment services using text mining method 김명숙, 김지연 p. 269-279
라즈베리파이를 활용한 블루투스 Smart Ready 구현 및 RSSI 오차 보정 = Bluetooth smart ready implementation and RSSI error correction using raspberry 이성진, 문상호 p. 280-286
(A) generation and accuracy evaluation of common metadata prediction model using public bicycle data and imputation method Jong-Chan, Kim, Se-Hoon, Jung p. 287-296
9축센서 기반의 도로시설물 충돌감지 알고리즘 = Collision detection algorithm using a 9-axis sensor in road facility 홍기현, 이병문 p. 297-310
비전공자 대상 SW/AI 기초 교양 교육을 위한 ARCS-DEVS모델 기반의 프로그래밍 학습방법 연구 = A study on ARCS-DEVS-based programming learning methods for SW/AI basic liberal arts education for non-majors 한영신 p. 311-324
디지털 트윈을 활용한 실시간 모니터링 및 원격제어 시스템의 테스트베드 구현 = Implementation of real-time monitoring and remote control system testbed based on digital twin 윤정은, 김원석 p. 325-334
인터넷 구전 정보가 전자상거래 생방송에서 소비자 구매 의도에 미치는 영향 = The influence of Internet word of mouth information on consumers' purchase intention in e-commerce live broadcast 추장운, 왕서일, 김치용 p. 335-344
빅데이터 활용 의학·바이오 부문 사업화 가능 기술 연구 = Research on the development of demand for medical and bio technology using big data 이봉문, 남가영, 강병철, 김치용 p. 345-352
소설 및 게임의 트랜스미디어에서 시각적 요소 분석 : Analysis of visual elements in transmedia of novels and games : focus on the worldview and characters of the original "Zhu Xian" / 원작 "주선"의 세계관과 캐릭터를 중심으로 서위영, 김치용 p. 353-362
인체 유래 환경유해물질 노출에 따른 멀티 오믹스 데이터 통합 분석 가시화 시스템 = Visualization for integrated analysis of multi-omics data by harmful substances exposed to human 신가희, 홍지만, 박서우, 강병철, 이봉문 p. 363-373
시선추적장치(Eye Tracking)를 활용한 인공지능(AI) 창작물과 사람의 창작물에 대한 시지각 비교 연구 = Comparative study on visual and perceptual difference towards the artworks of human and artificial intelligence using eye-tracking 황미경, 주이모, 박민희, 권만우 p. 374-381
전자상거래 생방송에서 IWOM과 구매의도의 관계에서 상호작용의 매개역할 = The mediating role of interaction in the relationship between IWOM and purchase intention e-commerce live broadcast 추장운, 김치용 p. 382-389
어포던스 이론에 기반한 제품 모델링 디자인 및 평가 연구 = Product modeling design and evaluation research based on affordance theory 진자죽, 김치용 p. 390-397
무형문화유산 앱 사용자 경험 최적화에 관한 연구 = A research on optimizing the user experience of intangible cultural heritage app 모평정, 조동민 p. 398-410
영화 <1917>의 게임적 체험 연구 : A study on the gaming experience of the movie <1917> : focused on the digital moving long take shot / 디지털 무빙 롱테이크 쇼트를 중심으로 유우현, 정원식 p. 411-420
Designing real-time observation system to evaluate driving pattern through eye tracker Kwekam Tchomdji Luther. Oberlin, Euitay, Jung p. 421-431
효용이론 기반 숙고형 행동트리를 이용한 게임 인공지능 에이전트 = Game AI agents using deliberative behavior tree based on utility theory 권민지, 서진석 p. 432-439
Exploiting neural network for temporal multi-variate air quality and pollutant prediction Muneeb A. Khan, Hyun-chul Kim, Heemin Park p. 440-449

참고문헌 (17건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 K.T. Cha, S.S. Oh, J.H. Yoon, K.H. Lee, S.K. Kim, B.S. Cha S.H. Kim et al., “Adverse Health Outcomes in Residents Exposed to Cement Dust,” Toxicology and Environmental Health Sciences, Vol. 3. pp. 239-244, 2011. 미소장
2 F. Grun and B. Blumberg, “Environmental Obesogens: Organotinsand Endocrine Disruption via Nuclear Receptor Signaling,”Endocrinology, Vol. 147, pp. S50-S55, 2006. 미소장
3 R. Vermeulen, E.L. Schymanski, A.L. Barabási, and G.W. Miller, “The Exposome and Health: Where Chemistry Meets Biology,”Science. Vol. 367, No. 6476, pp. 392-396, 2020. 미소장
4 S.B. Koh, “Environmental Diseases,” Journal of the Korean Medical Association, Vol. 55, No. 3, pp. 212-213, 2012 미소장
5 O. Robinson and M. Vrijheid, “The Pregnancy Exposome,” Current Environmental Health Report, Vol. 2, pp. 204-213, 2015. 미소장
6 K.A. Thayer, J.J. Heindel, J.R. Bucher, and M.A. Gallo, “Role of Environmental Chemicals in Diabetes and Obesity: a National Toxicology Program Workshop Review,” Environmental Health Perspectives, Vol. 120, pp. 779-789, 2012. 미소장
7 M.M. Niedzwiecki, D.I. Walker, R. Vermeulen, M. Chadeau-Hyam, D.P. Jones, and G.W. Miller, “The Exposome: Molecules to Populations,”Annual Review of Pharmacology and Toxicology, Vol. 59, pp. 107-127, 2019. 미소장
8 C.P. Wild, “Complementing the Genome with an “Exposome”: The Outstanding Challenge of Environmental Exposure Measurement in Molecular Epidemiology,” Cancer Epidemiology Biomarkers &Prevention, Vol. 14, No. 8, pp. 1847-1850, 2005. 미소장
9 R. Hernández-de-Diego, S. Tarazona, C. Martínez-Mira, L. Balzano-Nogueira, P. Furió-Tarí, G.J. Pappas et al., “PaintOmics3: a Web Resource for the Pathway Analysis and Visualization of Multi-omics Data,” Nucleic Acids Research. Vol. 46, pp. W503-W509, 2018. 미소장
10 J. Gao, B.A. Aksoy, U. Dogrusoz, G. Dresdner, B. Gross, S.O. Sumer et al., “Integrative Analysis of Complex Cancer Genomics and Cinical Profiles Using the cBioPortal,” Science Signaling. Vol. 6, p. pl1, 2013. 미소장
11 M.J. Goldman, B, Craft, M. Hastie, K. Repečka, F. McDade, A. Kamath et al., “Visualizing and Interpreting Cancer Genomics Data via the Xena Platform,” Nature Biotechnology. Vol. 38, pp. 675-678, 2020. 미소장
12 S.V. Vasaikar, P. Straub, J. Wang, and B. Zhang, “LinkedOmics: Analyzing Multi-Omics Data within and across 32 Cancer Types,”Nucleic Acids Research. Vol. 46, pp. D956-D963, 2018. 미소장
13 R. Ihaka and R. Gentleman, “R: a Language for Data Analysis and Graphics,” Journal of Computational and Graphical Statistics, Vol. 5, No. 3, pp. 299-314, 1996. 미소장
14 E. Bonnet, L. Calzone, and T. Michoel, “Integrative Multi-Omics Module Network Inference with Lemon-Tree,” PLoS Computational Biology, Vol. 11, No. 2, pp. e1003983, 2015. 미소장
15 R. Argelaguet, B. Velten, D. Arnol, S. Dietrich, T. Zenz, J.C. Marioni et al., “Multi-Omics Factor Analysis—a Framework for Unsupervised Integration of Multi-Omics Data Sets,”Molecular Systems Biology, Vol. 14, No. 6, pp. 8124, 2018. 미소장
16 J. Nicodemus-Johnson, R.A. Myers, N.J. Sakabe, D.R. Sobreira, D.K. Hogarth, E.T. Naureckas et al., “DNA Methylation in Lung Cells is Associated with Asthma Endotypes and Genetic Risk,” The Journal of Clinical Investigation Insight, Vol. 1, No. 20, pp. 90151, 2016. 미소장
17 Y. Park and Y. Lee, “A Study on Countermeasure for Privacy in Mobile Office,” Journal of Korea Multimedia Society, Vol. 18, No. 2, pp. 178-188, 2015. 미소장

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