Computational meta'omics for microbial community studies.

Computational meta'omics for microbial community studies.
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微生物社区研究的计算元杂志。

DOI:
10.1038/msb.2013.22
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发表时间:
2013-05-14
影响因子:
9.9
通讯作者:
--
中科院分区:
生物学1区
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--
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复杂的微生物群落是地球生态系统和我们身体健康和疾病的组成部分。在过去的二十年中,不依赖培养的方法为它们的结构和功能提供了新的见解,高通量测序的成本呈指数级下降,从而为微生物调查提供了广泛可用的工具。然而,该领域仍然远远没有达到技术平台,因为微生物基因组和转录内容的计算技术和核苷酸测序平台都在不断改进。因此,目前的微生物组分析开始采用多种互补的Meta组学方法,从而为全面准确地表征微生物群落及其与环境和宿主的相互作用带来了前所未有的机会。这种可用的测定、分析方法和公共数据的多样性反过来又开始使基于微生物组的预测和建模工具成为可能。因此,我们在这里审查的技术和计算Meta组学的方法,已经可用,那些正在积极发展,他们在生物发现的成功,和几个突出的挑战。
Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.
使用通用的unifrac距离将微生物组组成与环境协变量相关联。
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