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Big Data Biology: Between Eliminative Inferences and Exploratory Experiments

Published online by Cambridge University Press:  01 January 2022

Emanuele Ratti
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Abstract

Recently, biologists have argued that data-driven biology fosters a new scientific methodology, namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data-driven studies can be included in the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful generalizations to complement the procedure of prioritization. Overall, this article aims to shed light on the structure of contemporary research in molecular biology.

Type
Research Article
Information
Philosophy of Science , Volume 82 , Issue 2 , April 2015 , pp. 198 - 218
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

I am extremely grateful to the fellows of the PhD program FOLSATEC (especially Pierre Luc Germain, Federico Boem, Marco Annoni, and Giovanni Boniolo) for their valuable comments on previous drafts, as well as to Michael Weisberg and his group in Philadelphia (especially Emily Parke, Carlos Santana, Jane Reznik, and Alkistis Elliot-Graves). I am in debt also to David Teira for his indispensable comments on advanced drafts.

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