虚假关系
模块化(生物学)
生物
推论
背景(考古学)
微生物群
生物网络
利基
网络分析
生态学
数据科学
生态位
计算生物学
计算机科学
人工智能
机器学习
进化生物学
生物信息学
量子力学
物理
古生物学
栖息地
作者
Lisa Röttjers,Karoline Faust
出处
期刊:Fems Microbiology Reviews
[Oxford University Press]
日期:2018-07-25
卷期号:42 (6): 761-780
被引量:463
标识
DOI:10.1093/femsre/fuy030
摘要
Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these networks is not straightforward, and the biological implications of network properties are unclear. Analysis of microbial networks allows researchers to predict hub species and species interactions. Additionally, such analyses can help identify alternative community states and niches. Here, we review factors that can result in spurious predictions and address emergent properties that may be meaningful in the context of the microbiome. We also give an overview of studies that analyse microbial networks to identify new hypotheses. Moreover, we show in a simulation how network properties are affected by tool choice and environmental factors. For example, hub species are not consistent across tools, and environmental heterogeneity induces modularity. We highlight the need for robust microbial network inference and suggest strategies to infer networks more reliably.
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