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공공누리This item is licensed Korea Open Government License

초고성능컴퓨팅 기반 건강한 고령사회 대응 빅데이터 기술 개발
Alternative Title
Development of biomedical data network analysis technology based on high performance computing for dementia researches
Korea Institute of Science and Technology Information
Publication Year
funder : 미래창조과학부
funder : KA
본 연구과제의 목적은 HPC(High Performance Computing) 및 데이터 기반의 질병 연구를 위한 분석 기술의 개발임. 이를 위해, 본 연구과제는 당해 연도에 다음과 같이 수행되었음.
○ 노인성 치매 대응을 위한 치매 데이터 네트워크 분석 기술 확보
○ 치매 발병 메커니즘에 대한 가상 실험을 위한 모델링 및 시뮬레이션 기술 개발
○ 치매 연구 지원 시스템 개발 및 확산
○ 감염병 대응을 위한 변이 및 확산 예측 기술 개발

Ⅳ. Results of the study
○ Research and development for the biological network analysis
-Development of the novel clustering and sub-network matching algorithms based on Spark platform (increase of clustering and sub-network matching execution time compared to MCL(134%) and PVF2(120%), respectively)
-Identification of essential genes(15 gene) that is related to Alzheimer's disease with the gene expression data

○ Biological network modeling and simulation
-Construction of the global gene regulatory network (13,141 node and 32,763 edge)
-Development of boolean simulation tool (increase of simulation performance compared to BoolNet up to 10 fold)

○ Development and application of the prototype analysis platform on network and genome data for Alzheimer's disease research
-Research on text mining algorithm with using CNN algorithm to extract biological entity(F-score: 78.03%) and relation(F-score: 38.8%)
-Collection of somatic mutation information (54 Alzheimer's disease brain sample)
-Development of the prototype analysis systems based on the big data processing platform with web interface (user’s satisfaction score: 91.2 points)

○ Development of the prediction techniques based on big data
-Gathering the opinions of the experts from organization, research institute, universities through opening a seminar for cooperation with influenza and virus team in NIH, a seminar for using big data with National Health Insurance Service, 2 seminars about influenza mutation analysis techniques based on experiments and disease prediction techniques using machine learning models
-Handle 2 new major consignment tasks using disease mutation and prediction core techniques
-Collecting big data on disease emergence and development of processing and visualizing platform
치매 탐색; 치매 데이터 네트워크; 데이터 네트워크; 데이터 마이닝; 바이오-메디컬 빅데이터; Dementia Screening; Dementia Data Network; Data Network; Data Mining; Bio-Medical Bigdata
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7. KISTI 연구성과 > 연구보고서 > 2017
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