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When one model is not enough: Combining epistemic tools in systems biology

Green, Sara (2013) When one model is not enough: Combining epistemic tools in systems biology. [Preprint]

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In recent years, the philosophical focus of the modeling literature has shifted from
descriptions of general properties of models to an interest in different model functions. It has
been argued that the diversity of models and their correspondingly different epistemic goals
are important for developing intelligible scientific theories (Levins, 2006; Leonelli, 2007).
However, more knowledge is needed on how a combination of different epistemic means can
generate and stabilize new entities in science. This paper will draw on Rheinberger’s
practice-oriented account of knowledge production. The conceptual repertoire of
Rheinberger’s historical epistemology offers important insights for an analysis of the
modelling practice. I illustrate this with a case study on network modeling in systems biology
where engineering approaches are applied to the study of biological systems. I shall argue
that the use of multiple means of representations is an essential part of the dynamic of
knowledge generation. It is because of – rather than in spite of – the diversity of constraints
of different models that the interlocking use of different epistemic means creates a potential
for knowledge production.

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Item Type: Preprint
Keywords: modeling, reverse engineering, network motifs, Rheinberger, engineering analogies, historical epistemology.
Subjects: General Issues > Models and Idealization
Depositing User: Dr. Sara Green
Date Deposited: 18 Sep 2014 14:00
Last Modified: 18 Sep 2014 14:00
Item ID: 11030
Official URL:
Subjects: General Issues > Models and Idealization
Date: 2013

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