联合星系:生物医学计算的前沿。

Enis Afgan, Vahid Jalili, Nuwan Goonasekera, James Taylor, Jeremy Goecks
{"title":"联合星系:生物医学计算的前沿。","authors":"Enis Afgan, Vahid Jalili, Nuwan Goonasekera, James Taylor, Jeremy Goecks","doi":"10.1109/cloud.2018.00124","DOIUrl":null,"url":null,"abstract":"<p><p>Biomedical data exploration requires integrative analyses of large datasets using a diverse ecosystem of tools. For more than a decade, the Galaxy project (https://galaxyproject.org) has provided researchers with a web-based, user-friendly, scalable data analysis framework complemented by a rich ecosystem of tools (https://usegalaxy.org/toolshed) used to perform genomic, proteomic, metabolomic, and imaging experiments. Galaxy can be deployed on the cloud (https://launch.usegalaxy.org), institutional computing clusters, and personal computers, or readily used on a number of public servers (e.g., https://usegalaxy.org). In this paper, we present our plan and progress towards creating Galaxy-as-a-Service-a federation of distributed data and computing resources into a panoptic analysis platform. Users can leverage a pool of public and institutional resources, in addition to plugging-in their private resources, helping answer the challenge of resource divergence across various Galaxy instances and enabling seamless analysis of biomedical data.</p>","PeriodicalId":93366,"journal":{"name":"Proceedings. IEEE International Conference on Cloud Computing","volume":"2018 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356149/pdf/nihms-1689939.pdf","citationCount":"0","resultStr":"{\"title\":\"Federated Galaxy: Biomedical Computing at the Frontier.\",\"authors\":\"Enis Afgan, Vahid Jalili, Nuwan Goonasekera, James Taylor, Jeremy Goecks\",\"doi\":\"10.1109/cloud.2018.00124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Biomedical data exploration requires integrative analyses of large datasets using a diverse ecosystem of tools. For more than a decade, the Galaxy project (https://galaxyproject.org) has provided researchers with a web-based, user-friendly, scalable data analysis framework complemented by a rich ecosystem of tools (https://usegalaxy.org/toolshed) used to perform genomic, proteomic, metabolomic, and imaging experiments. Galaxy can be deployed on the cloud (https://launch.usegalaxy.org), institutional computing clusters, and personal computers, or readily used on a number of public servers (e.g., https://usegalaxy.org). In this paper, we present our plan and progress towards creating Galaxy-as-a-Service-a federation of distributed data and computing resources into a panoptic analysis platform. Users can leverage a pool of public and institutional resources, in addition to plugging-in their private resources, helping answer the challenge of resource divergence across various Galaxy instances and enabling seamless analysis of biomedical data.</p>\",\"PeriodicalId\":93366,\"journal\":{\"name\":\"Proceedings. IEEE International Conference on Cloud Computing\",\"volume\":\"2018 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356149/pdf/nihms-1689939.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE International Conference on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/cloud.2018.00124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/9/10 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Conference on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cloud.2018.00124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/9/10 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

生物医学数据探索需要使用多种工具对大型数据集进行综合分析。十多年来,银河项目(https://galaxyproject.org)为研究人员提供了一个基于网络、用户友好、可扩展的数据分析框架,并辅以丰富的工具生态系统(https://usegalaxy.org/toolshed),用于执行基因组、蛋白质组、代谢组和成像实验。银河系统可以部署在云端(https://launch.usegalaxy.org)、机构计算集群和个人电脑上,也可以在一些公共服务器(如 https://usegalaxy.org)上随时使用。在本文中,我们将介绍创建 "银河即服务"(Galaxy-as-a-Service)的计划和进展--"银河即服务 "是将分布式数据和计算资源整合为一个全景分析平台。用户除了插入自己的私人资源外,还可以利用公共资源和机构资源池,帮助应对不同银河实例之间资源差异的挑战,实现生物医学数据的无缝分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Federated Galaxy: Biomedical Computing at the Frontier.

Biomedical data exploration requires integrative analyses of large datasets using a diverse ecosystem of tools. For more than a decade, the Galaxy project (https://galaxyproject.org) has provided researchers with a web-based, user-friendly, scalable data analysis framework complemented by a rich ecosystem of tools (https://usegalaxy.org/toolshed) used to perform genomic, proteomic, metabolomic, and imaging experiments. Galaxy can be deployed on the cloud (https://launch.usegalaxy.org), institutional computing clusters, and personal computers, or readily used on a number of public servers (e.g., https://usegalaxy.org). In this paper, we present our plan and progress towards creating Galaxy-as-a-Service-a federation of distributed data and computing resources into a panoptic analysis platform. Users can leverage a pool of public and institutional resources, in addition to plugging-in their private resources, helping answer the challenge of resource divergence across various Galaxy instances and enabling seamless analysis of biomedical data.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
ArcaDB: A Disaggregated Query Engine for Heterogenous Computational Environments. Performance Evaluation of Modified Best First Decreasing Algorithms for Dynamic Virtual Machine Placement in Cloud Computing Improving Few-Shot Image Classification with Self-supervised Learning Cloud Computing - CLOUD 2022 - 15th International Conference, Held as Part of the Services Conference Federation, SCF 2022, Honolulu, HI, USA, December 10-14, 2022, Proceedings Optimizing Cache Accesses with Tensor Memory Format Search for Transformers in TVM
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1