The creative industry of integrative systems biology

Miles MacLeod () and Nancy Nersessian ()

Mind & Society: Cognitive Studies in Economics and Social Sciences, 2013, vol. 12, issue 1, 35-48

Abstract: Integrative systems biology (ISB) is among the most innovative fields of contemporary science, bringing together scientists from a range of diverse backgrounds and disciplines to tackle biological complexity through computational and mathematical modeling. The result is a plethora of problem-solving techniques, theoretical perspectives, lab-structures and organizations, and identity labels that have made it difficult for commentators to pin down precisely what systems biology is, philosophically or sociologically. In this paper, through the ethnographic investigation of two ISB laboratories, we explore the particular structural features of ISB thinking and organization and its relations to other disciplines that necessitate cognitive innovation at all levels from lab PI’s to individual researchers. We find that systems biologists face numerous constraints that make the production of models far from straight-forward, while at the same time they inhabit largely unstructured task environments in comparison to other fields. We refer to these environments as adaptive problem spaces. These environments they handle by relying substantially on the flexibility and affordances of model-based reasoning to integrate these various constraints and find novel adaptive solutions. Ultimately what is driving this innovation is a determination to construct new cognitive niches in the form of functional model building frameworks that integrate systems biology within the biological sciences. The result is an industry of diverse and different innovative practices and solutions to the problem of modeling complex, large-scale biological systems. Copyright Springer-Verlag Berlin Heidelberg 2013

Keywords: Integrative systems biology; Adaptive problem spaces; Cognitive niche construction; Model-based reasoning; Distributed cognition (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11299-013-0119-3

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