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:0960443
- 负责人:
- 金额:$ 32.26万
- 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 2014-06-30
- 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 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获得赠款,用于开发一个动态可扩展的协作社区G-SEESCENT Cloud,用于生物知识发现。该项目的第一个目标是在方法、功能、准确性、效率和可扩展性方面增强流行的G-SEESTING工具(http://bioinformatics.clemson.edu/G-SEESTING),以满足在日常生物研究中使用G-SEESTING工具的研究人员的迫切需求。最终目标是建立一个基于社区的可扩展的云计算基础设施(G-SEESDCloud),以帮助生物研究人员传播他们的研究成果。该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)将其在任何平台下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-SEESDCloud上。研究人员还可以使用本项目开发的配置实用程序轻松地将其计算设备配置到G-SEESCloud中。本项目将产生一套完整的Web服务,用于使用不同方法测量生物实体的功能相似性,并根据这些相似性值发现生物知识。G-SEESDIT云将提供一个基于社区,高效且可自我扩展的云计算环境,研究人员可以在其中轻松发布其生物应用软件即服务(SaaS),并共享其计算基础设施即服务(IaaS)。G-SEMPENDIX Cloud及其GO-基于Web服务将减轻生物学研究人员学习Web技术和维护自己的计算设施的负担,可以专注于他们的研究。该项目的成功将为构建可自扩展的基于社区的生物云提供范例,以促进生物研究社区的资源共享和SaaS,IaaS和PaaS(平台即服务)概念。该项目还将用于培训计算机科学专业的学生,包括女性和少数民族学生,学习分布式计算,数据挖掘和Web技术。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Philip Yu其他文献
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks
异构网络中多方面信息的深度协同过滤
- DOI:
10.1109/tkde.2019.2941938 - 发表时间:
2019-09 - 期刊:
- 影响因子:8.9
- 作者:
Chuan Shi;Xiaotian Han;Song Li;Xiao Wang;Senzhang Wang;Junping Du;Philip Yu - 通讯作者:
Philip Yu
OS105 - Training, validation and testing of a multiscale three-dimensional deep learning algorithm in accurately diagnosing hepatocellular carcinoma on computed tomography
OS105 - 用于在计算机断层扫描上准确诊断肝细胞癌的多尺度三维深度学习算法的训练、验证和测试
- DOI:
10.1016/s0168-8278(22)00551-7 - 发表时间:
2022-07-01 - 期刊:
- 影响因子:33.000
- 作者:
Wai-Kay Seto;Keith Wan Hang Chiu;Wenming Cao;Gilbert Lui;Jian Zhou;Ho Ming Cheng;Juan Wu;Xinping Shen;Lung Yi Loey Mak;Jinhua Huang;Wai Keung Li;Man-Fung Yuen;Philip Yu - 通讯作者:
Philip Yu
Efficient Reverse Nearest Neighbor Search in Trajectory-driven Services
轨迹驱动服务中的高效反向最近邻搜索
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Xiao Pan;Shili Nie;Haibo Hu;Philip Yu;Jingfeng Guo - 通讯作者:
Jingfeng Guo
WED-154 Artificial intelligence foundation models for histological diagnosis of hepatocellular carcinoma based on 121,344 digitalized whole slide image patches
WED - 154基于121344个数字化全切片图像块的肝细胞癌组织学诊断人工智能基础模型
- DOI:
10.1016/s0168-8278(25)01224-3 - 发表时间:
2025-05-01 - 期刊:
- 影响因子:33.000
- 作者:
Yan Miao;Philip Yu;Tak-Siu Wong;Regina Cheuk Lam Lo;Ho Ming Cheng;Lequan Yu;Lung-Yi Mak;Man-Fung Yuen;Wai-Kay Seto - 通讯作者:
Wai-Kay Seto
Hierarchical Representation Learning for Attributed Networks
属性网络的层次表示学习
- DOI:
10.1109/tkde.2021.3117274 - 发表时间:
2023-03 - 期刊:
- 影响因子:8.9
- 作者:
Shu Zhao;Ziwei Du;Jie Chen;Yanping Zhang;Jie Tang;Philip Yu - 通讯作者:
Philip Yu
Philip Yu的其他文献
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{{ truncateString('Philip Yu', 18)}}的其他基金
III: Medium: Collaborative Research: Self-Supervised Recommender System Learning with Application Specific Adaption
III:媒介:协作研究:具有特定应用适应性的自监督推荐系统学习
- 批准号:
2106758 - 财政年份:2021
- 资助金额:
$ 32.26万 - 项目类别:
Standard Grant
III: Small: Exploiting the Massive User Generated Utterances for Intent Mining under Scarce Annotations
III:小:利用大量用户生成的话语进行稀缺注释下的意图挖掘
- 批准号:
1909323 - 财政年份:2019
- 资助金额:
$ 32.26万 - 项目类别:
Standard Grant
SaTC: CORE: Small: Collaborative: Learning Dynamic and Robust Defenses Against Co-Adaptive Spammers
SaTC:核心:小型:协作:学习针对自适应垃圾邮件发送者的动态且强大的防御
- 批准号:
1930941 - 财政年份:2019
- 资助金额:
$ 32.26万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: An Extensible Heterogeneous Network Embedding Framework with Application Specific Adaptation
III:媒介:协作研究:具有特定应用适应能力的可扩展异构网络嵌入框架
- 批准号:
1763325 - 财政年份:2018
- 资助金额:
$ 32.26万 - 项目类别:
Continuing Grant
III: Small: Fusion of Heterogeneous Networks for Synergistic Knowledge Discovery
III:小:异构网络融合以实现协同知识发现
- 批准号:
1526499 - 财政年份:2015
- 资助金额:
$ 32.26万 - 项目类别:
Standard Grant
TC: Small: Robust Anonymization on Social Networks
TC:小:社交网络上强大的匿名化
- 批准号:
1115234 - 财政年份:2011
- 资助金额:
$ 32.26万 - 项目类别:
Standard Grant
III:Small:Privacy Preserving Data Publishing: A Second Look on Group based Anonymization
III:小:隐私保护数据发布:基于群体的匿名化的再审视
- 批准号:
0914934 - 财政年份:2009
- 资助金额:
$ 32.26万 - 项目类别:
Continuing Grant
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