Collaborative Research: G-SESAME Cloud: A Dynamically Scalable Collaboration Community for Biological Knowledge Discovery
协作研究:G-SESAME Cloud:用于生物知识发现的动态可扩展协作社区
基本信息
- 批准号:0960586
- 负责人:
- 金额:$ 54.55万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-07-01 至 2015-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Clemson University and the University of Illinois at Chicago are awarded grants to develop a dynamically scalable collaboration community, G-SESAME Cloud, for biological knowledge discovery. The first aim of this project is to enhance the popular G-SESAME (Gene Semantic Similarity Analysis and Measurement) tools (http://bioinformatics.clemson.edu/G-SESAME) in terms of methodology, functionality, accuracy, efficiency, and scalability to address the immediate needs of researchers who utilize G-SESAME tools in their daily biological research. The ultimate goal is to build a community-based scalable cloud computing infrastructure (G-SESAME Cloud) to help the biological researchers disseminate their research results. This infrastructure will provide a set of Web-based tools for biological researchers to automatically (or semi-automatically) convert their GO-based biological programs developed in any programming languages under any platforms into Web services and publish them on the G-SESAME Cloud. Researchers can also use a configuration utility developed in this project to easily configure their computing facilities into the G-SESAME Cloud.This project will produce a complete set of Web services for measuring the functional similarity of biological entities using different methods, and for discovering biological knowledge based on such similarity values. The G-SESAME Cloud will provide a community-based, effective and self-scalable cloud computing environment in which researchers can easily publish their biological application software as a service (SaaS) and share their computing infrastructure as a service (IaaS).The G-SESAME Cloud and its GO-based Web services will release the burden of biological researchers from learning Web technologies and maintaining their own computing facilities so that they can focus on their research. The success of this project will set an example for building self-scalable community-based biological Cloud to promote resource sharing and SaaS, IaaS and PaaS (Platform as a Service) concepts in biological research community. This project will also be used to train Computer Science students, including women and minority students, on distributed computing, data mining, and Web technologies.
克莱姆森大学和伊利诺伊大学芝加哥分校被授予赠款,以开发一个动态可扩展的合作社区G-芝麻云,用于生物学知识发现。本项目的第一个目标是在方法学、功能性、准确性、效率和可扩展性方面增强流行的G-SESAME(基因语义相似性分析和测量)工具(http://bioinformatics.clemson.edu/G-SESAME)),以满足在日常生物学研究中使用G-SESAME工具的研究人员的迫切需求。最终目标是构建一个基于社区的可扩展云计算基础设施(G-Sesame Cloud),帮助生物研究人员传播他们的研究成果。这一基础设施将为生物研究人员提供一套基于Web的工具,以自动(或半自动)将他们在任何平台上以任何编程语言开发的基于GO的生物程序转换为Web服务,并将其发布在G-Sesame Cloud上。研究人员还可以使用该项目开发的配置实用程序来轻松地将他们的计算设施配置到G-Sesame云中。该项目将产生一套完整的Web服务,用于使用不同的方法测量生物实体的功能相似性,并基于这些相似性值发现生物知识。G-芝麻云将提供一个基于社区的、高效的、可自我扩展的云计算环境,在这个环境中,研究人员可以轻松地将他们的生物应用软件作为服务(SaaS)发布,并将他们的计算基础设施作为服务(IaaS)共享。G-芝麻云及其基于Go的Web服务将把生物研究人员从学习Web技术和维护自己的计算设施中解脱出来,以便他们能够专注于自己的研究。该项目的成功将为构建可自我扩展的基于社区的生物云,促进生物研究社区的资源共享和SaaS、IaaS和PaaS(平台即服务)理念树立榜样。该项目还将用于培训计算机科学专业的学生,包括女性和少数族裔学生,学习分布式计算、数据挖掘和网络技术。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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Zijun Wang其他文献
Organizational Distance Also Matters: A Case Study of Distributed Research Teams and their Paper Productivity
组织距离也很重要:分布式研究团队及其论文生产力的案例研究
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Dakuo Wang;M. Muller;Qian Yang;Zijun Wang;Ming Tan;Stacy F. Hobson - 通讯作者:
Stacy F. Hobson
External equity in agriculture: Risk sharing and incentives in a principal‐agent relationship
农业外部股权:委托代理关系中的风险分担和激励
- DOI:
10.1108/00214850280001126 - 发表时间:
2002 - 期刊:
- 影响因子:0
- 作者:
Zijun Wang;D. Leatham;Thanapat Chaisantikulawat - 通讯作者:
Thanapat Chaisantikulawat
STAT3/Mitophagy Axis Coordinates Macrophage NLRP3 Inflammasome Activation and Inflammatory Bone Loss
STAT3/线粒体自噬轴协调巨噬细胞NLRP3炎症小体激活和炎症性骨质流失
- DOI:
10.1002/jbmr.4756 - 发表时间:
2022-12 - 期刊:
- 影响因子:6.2
- 作者:
Lingxin Zhu;Zijun Wang;Xiaoyue Sun;Jingjing Yu;Ting Li;Huan Zhao;Yaoting Ji;Bin Peng;Minquan Du - 通讯作者:
Minquan Du
A model selection approach to jointly testing for structural breaks and cointegration with application to the Eurocurrency interest rates market
联合测试结构性断裂和协整的模型选择方法,并应用于欧洲货币利率市场
- DOI:
10.1007/s00181-020-01916-1 - 发表时间:
2020 - 期刊:
- 影响因子:3.2
- 作者:
Yanxiang Qian;Zijun Wang - 通讯作者:
Zijun Wang
Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models
在高能物理中使数字对象公平:通用 FeynRules 输出 (UFO) 模型的实现
- DOI:
10.21468/scipostphyscodeb.13 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
M. Neubauer;Avik Roy;Zijun Wang - 通讯作者:
Zijun Wang
Zijun Wang的其他文献
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