The use of molecules and reactions as evidence, markers and/or traits for evolutionary processes has a history more than a century long. Molecules have been used in studies of intra-specific variation and studies of similarity among species that do not necessarily result in the analysis of phylogenetic relations. Promoters of the use of molecular data have sustained the need for quantification as the main argument to make use of them. Moreover, quantification has allowed intensive statistical analysis, as a condition and (...) a product of increasing automation. All of these analyses are subject to the methodological anxiety characteristic of a community in search of objectivity. It is in this context that scientists compared and evaluated protein and nucleic acid sequence data with other types of molecular data – including immunological, electrophoretic and hybridization data. This paper argues that by looking at long-term historical processes, such as the use of molecular evidence in evolutionary biology, we gain valuable insights into the history of science. In that sense, it accompanies a growing concern among historians for big-pictures of science that incorporate the fruitful historical research on local cases of the last decades. (shrink)

Although the interdisciplinary nature of contemporary biological sciences has been addressed by philosophers, historians, and sociologists of science, the different ways in which engineering concepts and methods have been applied in biology have been somewhat neglected. We examine - using the mechanistic philosophy of science as an analytic springboard - the transfer of network methods from engineering to biology through the cases of two biology laboratories operating at the California Institute of Technology. The two laboratories study gene regulatory networks, but (...) in remarkably different ways. The research strategy of the Davidson lab fits squarely into the traditional mechanist philosophy in its aim to decompose and reconstruct, in detail, gene regulatory networks of a chosen model organism. In contrast, the Elowitz lab constructs minimal models that do not attempt to represent any particular naturally evolved genetic circuits. Instead, it studies the principles of gene regulation through a template-based approach that is applicable to any kinds of networks, whether biological or not. We call for the mechanists to consider whether the latter approach can be accommodated by the mechanistic approach, and what kinds of modifications it would imply for the mechanistic paradigm of explanation, if it were to address modelling more generally. (shrink)