Philosophy of Science 83 (5):921-933 (2016)

Authors
Marie I. Kaiser
Bielefeld University
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.
Keywords Causation  Complexity
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Reprint years 2014, 2016
DOI 10.1086/687875
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References found in this work BETA

Causality.Judea Pearl - 2000 - Cambridge University Press.
Making Things Happen. A Theory of Causal Explanation.Michael Strevens - 2007 - Philosophy and Phenomenological Research 74 (1):233-249.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.

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Citations of this work BETA

Establishing Causal Claims in Medicine.Jon Williamson - 2019 - International Studies in the Philosophy of Science 32 (1):33-61.

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