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

Philosophy of Science 83 (5):921-933 (2016)
Download Edit this record How to cite View on PhilPapers
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.
Reprint years
2014, 2016
PhilPapers/Archive ID
Upload history
Archival date: 2017-02-17
View other versions
Added to PP index

Total views
213 ( #34,644 of 71,328 )

Recent downloads (6 months)
27 ( #30,994 of 71,328 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.