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Systems biology, synthetic biology and data-driven research: A commentary on Krohs, Callebaut, and O’Malley and Soyer

Calvert, J

Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences   43 (1) 81-84

March 2012

The three papers that I will discuss here all focus on systems biology. This is significant in the context of data-driven research, because systems biology is the approach to biology which explicitly attempts to make sense of the vast amounts of ‘omics’ data generated by high-throughput techniques. Two of the three papers (Callebaut, 2012 and O’Malley and Soyer, 2012) additionally address synthetic biology. Systems and synthetic biology have much in common, and both can be interpreted as attempts to deliver on the promises of the genome sequencing projects, in respect to both biological understanding and applications (Calvert & Fujimura, 2011). The two fields do have important differences in their orientation and aims, however, and I will return to this point in my discussion of engineering below.

The three papers came out of a workshop on ‘Data-driven research in the biological and biomedical sciences’. The workshop was motivated by questions such as: Is data-driven research leading to changes in the ways in which biology is done? How should we understand these changes? What epistemological issues do they raise? Where do they leave hypothesis-driven research? And how do these developments challenge current thinking in the philosophy, history and sociology of science? As I understood it, the overarching aim of the workshop was to attempt to “come to grips philosophically with the transformations of biology in this century” (Callebaut, 2012, p. 75).