On the Limits of Causal Modeling: Spatially-Structurally Complex Biological Phenomena

Philosophy of Science 83 (5):921-933 (2016)
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Abstract
This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of these models is due to their failure to include relevant spatial and structural information in a way that does not render the model non-explanatory, unmanageable, or inconsistent with basic assumptions of causal graph theory.
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2014, 2016
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KAIOTL
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Archival date: 2017-02-17
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References found in this work BETA
Causality.Pearl, Judea
Causation, Prediction, and Search.Spirtes, Peter; Glymour, Clark & Scheines, Richard

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Citations of this work BETA
Intervening Into Mechanisms: Prospects and Challenges.Kästner, Lena & Andersen, Lise Marie

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