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Development of Multidimensional Analysis System for Bio-pathways

바이오 패스웨이 다차원 분석 시스템 개발

  • 서동민 (한국과학기술정보연구원 소프트웨어연구센터 과학기술마이닝팀) ;
  • 최윤수 (한국과학기술정보연구원 소프트웨어연구센터 과학기술마이닝팀) ;
  • 전선희 (한국과학기술정보연구원 소프트웨어연구센터 과학기술마이닝팀) ;
  • 이민호 (한국과학기술정보연구원 소프트웨어연구센터 과학기술마이닝팀)
  • Received : 2014.10.16
  • Accepted : 2014.11.04
  • Published : 2014.11.28

Abstract

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

Keywords

KEGG Pathway;Network Analysis;Big-Data;Cluster

Acknowledgement

Grant : 고성능 컴퓨팅 기반 빅데이터 기술 개발

Supported by : 한국과학기술정보연구원, 한국연구재단

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