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Information channels and biomarkers of disease

Illari, Phyllis and Russo, Federica (2016) Information channels and biomarkers of disease. [Preprint]

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Abstract

Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson (2012) address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has examined Ned Hall’s distinction between two concepts of causality: production and dependence (Hall, 2004). In another recent paper, Illari (2011b) examined the relatively under-explored production approach to causality, arguing
that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible
account of the nature of the causal link in biomarkers research, while an informational account is very promising.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Illari, Phyllis0000-0002-4211-3332
Russo, Federica
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Causation
Specific Sciences > Medicine
Depositing User: Dr Phyllis Illari
Date Deposited: 28 Sep 2018 17:33
Last Modified: 28 Sep 2018 17:33
Item ID: 15073
Official URL: https://link.springer.com/article/10.1007/s11245-0...
DOI or Unique Handle: https://doi.org/10.1007/s11245-013-9228-1
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Causation
Specific Sciences > Medicine
Date: 2016
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/15073

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