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本文引用的文献

1
How Does One "Open" Science? Questions of Value in Biological Research.如何“开放”科学?生物学研究中的价值问题。
Sci Technol Human Values. 2017 Mar;42(2):280-305. doi: 10.1177/0162243916672071. Epub 2016 Oct 4.
2
Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.代谢组学数据流:将数据处理和分析时间从数天缩短至数分钟。
Anal Chem. 2017 Jan 17;89(2):1254-1259. doi: 10.1021/acs.analchem.6b03890. Epub 2017 Jan 3.
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Interactive and scalable biology cloud experimentation for scientific inquiry and education.用于科学探究与教育的交互式可扩展生物学云实验。
Nat Biotechnol. 2016 Dec 7;34(12):1293-1298. doi: 10.1038/nbt.3747.
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Secure cloud computing for genomic data.用于基因组数据的安全云计算。
Nat Biotechnol. 2016 Jun 9;34(6):588-91. doi: 10.1038/nbt.3496.
5
Metabolomics: beyond biomarkers and towards mechanisms.代谢组学:超越生物标志物,迈向作用机制研究
Nat Rev Mol Cell Biol. 2016 Jul;17(7):451-9. doi: 10.1038/nrm.2016.25. Epub 2016 Mar 16.
6
MetaboAnalyst 3.0--making metabolomics more meaningful.MetaboAnalyst 3.0——让代谢组学更具意义。
Nucleic Acids Res. 2015 Jul 1;43(W1):W251-7. doi: 10.1093/nar/gkv380. Epub 2015 Apr 20.
7
Multi-omic data analysis using Galaxy.使用Galaxy进行多组学数据分析。
Nat Biotechnol. 2015 Feb;33(2):137-9. doi: 10.1038/nbt.3134.
8
Metabolomic data streaming for biology-dependent data acquisition.用于依赖生物学的数据采集的代谢组学数据流
Nat Biotechnol. 2014 Jun;32(6):524-7. doi: 10.1038/nbt.2927.
9
Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI).化学分析最低报告标准建议 化学分析工作组(CAWG)代谢组学标准倡议(MSI)
Metabolomics. 2007 Sep;3(3):211-221. doi: 10.1007/s11306-007-0082-2.
10
Biology: The big challenges of big data.生物学:大数据的巨大挑战。
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在云端处理代谢数据。

Metabolizing Data in the Cloud.

作者信息

Warth Benedikt, Levin Nadine, Rinehart Duane, Teijaro John, Benton H Paul, Siuzdak Gary

机构信息

Center for Metabolomics and Departments of Chemistry, Molecular and Computational Biology, Immunology and Microbial Science and Chemical Physiology, The Scripps Research Institute, La Jolla, CA, USA.

Center for Metabolomics and Departments of Chemistry, Molecular and Computational Biology, Immunology and Microbial Science and Chemical Physiology, The Scripps Research Institute, La Jolla, CA, USA.

出版信息

Trends Biotechnol. 2017 Jun;35(6):481-483. doi: 10.1016/j.tibtech.2016.12.010. Epub 2017 Jan 20.

DOI:10.1016/j.tibtech.2016.12.010
PMID:28117091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8889625/
Abstract

Cloud-based bioinformatic platforms address the fundamental demands of creating a flexible scientific environment, facilitating data processing and general accessibility independent of a countries' affluence. These platforms have a multitude of advantages as demonstrated by omics technologies, helping to support both government and scientific mandates of a more open environment.

摘要

基于云的生物信息学平台满足了创建灵活科学环境的基本需求,促进了数据处理,并实现了不受国家富裕程度影响的普遍可及性。正如组学技术所展示的那样,这些平台具有众多优势,有助于支持政府和科学界对更开放环境的要求。