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Multivariate statistics and the enactment of metabolic complexity

机译:多元统计和代谢复杂性的制定

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This ethnographic study, based on fieldwork at the Computational and Systems Medicine laboratory at Imperial College London, shows how researchers in the field of metabolomics -the post-genomic study of the molecules and processes that make up metabolism - enact and coproduce complex views of biology with multivariate statistics. From this data-driven science, metabolism emerges as a multiple, informational and statistical object, which is both produced by and also necessitates particular forms of data production and analysis. Multivariate statistics emerge as 'natural' and 'correct' ways of engaging with a metabolism that is made up of many variables. In this sense, multivariate statistics allow researchers to engage with and conceptualize metabolism, and also disease and processes of life, as complex entities. Consequently, this article builds on studies of scientific practice and visualization to examine data as material objects rather than black-boxed representations. Data practices are not merely the technological components of experimentation, but are simultaneously technologies and methods and are intertwined with ways of seeing and enacting the biological world. Ultimately, this article questions the increasing invocation and role of complexity within biology, suggesting that discourses of complexity are often imbued with reductionist and determinist ways of thinking about biology, as scientists engage with complexity in calculated and controlled, but also limited, ways.
机译:这项民族志研究基于伦敦帝国理工学院计算和系统医学实验室的实地调查,显示了代谢组学领域的研究人员-组成代谢的分子和过程的后基因组研究-如何制定并共同产生生物学的复杂观点具有多元统计量。从这种数据驱动的科学中,新陈代谢是一个多重的,信息性的和统计性的对象,它既是由数据生产和分析的特殊形式产生的,又有必要的。多元统计数据以参与多种新陈代谢的“自然”和“正确”方式出现。从这个意义上讲,多元统计数据使研究人员可以将代谢以及疾病和生命过程作为复杂的实体进行参与和概念化。因此,本文基于对科学实践和可视化的研究,将数据作为实质对象而不是黑盒表示形式进行检查。数据实践不仅是实验的技术组成部分,而且是同时的技术和方法,并与观察和实现生物世界的方式交织在一起。最终,本文对生物学中复杂性的呼唤和作用提出了质疑,这表明,随着科学家以计算和控制的方式,但也是有限的方式从事复杂性研究,复杂性话语通常充满着还原论和确定论的生物学思维方式。

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