To improve the research productivity in bioinformatics study by using effective means of large scale data analysis, there are many obstacles that need to be overcome They are standardization of data collection and analysis, management of computing and storage resources, easiness of parallel programming, and efficiency of data analysis job execution, to name a few. Among these, easiness of parallel programming is a crucial factor that contributes to usability and efficiency of large scale data analysis. This paper describes a biologic data analysis platform based on cloud computing infrastructure. The platform provides an easy-to-use parallel data analysis environment, and ultimately enhances the productivity of bioinformatics research.
목차
Abstract 1. Introduction 2. Requirements of BioDAP 3. Design of BioDAP 3.1. Virtual Infrastructure 3.2. Biologic Data Integration System 3.3. Data Set and Provenance Management System 3.4. Data Analysis Programming Environment 3.5. Analysis Pipeline Execution Engine 4. Related Work 5. Conclusions Acknowledgements References
키워드
cloud computingparallel programmingbiologic data analysisdata management
저자
Hoon Choi [ Korea Institute of Science and Technology Information ]
Sang-Hwan Lee [ Korea Institute of Science and Technology Information ]
Dong-In Park [ Korea Institute of Science and Technology Information ]
보안공학연구지원센터(IJBSBT) [Science & Engineering Research Support Center, Republic of Korea(IJBSBT)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Bio-Science and Bio-Technology
간기
격월간
pISSN
2233-7849
수록기간
2009~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Bio-Science and Bio-Technology Vol.5 No.3