Systems Biology and Mechanistic Explanation

In Stuart Glennan & Phyllis McKay Illari (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. New York: Routledge. pp. 362–374 (2018)
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Abstract

We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction strategies serve various aims, including prediction and control, that are central to understanding the epistemic diversity of systems biology.

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Author Profiles

Ingo Brigandt
University of Alberta
Sara-Lee Green
Lund University

Citations of this work

Getting Over Atomism: Functional Decomposition in Complex Neural Systems.Daniel C. Burnston - 2021 - British Journal for the Philosophy of Science 72 (3):743-772.
The Non-Mechanistic Option: Defending Dynamical Explanations.Russell Meyer - 2020 - British Journal for the Philosophy of Science 71 (3):959-985.
The Nonmechanistic Option: Defending Dynamical Explanation.Russell Meyer - 2018 - British Journal for the Philosophy of Science:0-0.
Contemporary Hylomorphisms: On the Matter of Form.Christopher J. Austin - 2020 - Ancient Philosophy Today 2 (2):113-144.

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References found in this work

Explaining the Brain.Carl F. Craver - 2007 - Oxford University Press.
Explanation: A Mechanist Alternative.William Bechtel & Adele Abrahamsen - 2005 - Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):421-441.
What Makes a Scientific Explanation Distinctively Mathematical?Marc Lange - 2013 - British Journal for the Philosophy of Science 64 (3):485-511.

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