Abstract
This paper, which is based on recent empirical research at the University of Leeds, the University of Edinburgh, and the University of Bristol, presents two difficulties which arise when condensed matter physicists interact with molecular biologists: (1) the former use models which appear to be too coarse-grained, approximate and/or idealized to serve a useful scientific purpose to the latter; and (2) the latter have a rather narrower view of what counts as an experiment, particularly when it comes to computer simulations, than the former. It argues that these findings are related; that computer simulations are considered to be undeserving of experimental status, by molecular biologists, precisely because of the idealizations and approximations that they involve. The complexity of biological systems is a key factor. The paper concludes by critically examining whether the new research programme of ‘systems biology’ offers a genuine alternative to the modelling strategies used by physicists. It argues that it does not.
Original language | English |
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Pages (from-to) | 145-154 |
Number of pages | 10 |
Journal | Studies in History and Philosophy of Biological and Biomedical Sciences |
Volume | 42 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jun 2011 |
Externally published | Yes |
Bibliographical note
I am grateful to Alexander Bird for comments on an embryonic version, as well as to my other collaborators on the project—Wilson Poon, Tom McLeish, and Greg Radick—for their help and advice. I am also grateful for the comments of audience members at the ‘Physics Meets Biology’ conference held in order to mark the culmination of the project, especially Otávio Bueno, Mike Cates, Steven French, Evelyn Fox Keller, and Michel Morange. Finally, I owe my thanks to Alexander Bird and Jane Calvert for acting in an editorial capacity for this paper, and to the anonymous referees that they selected for their insightful criticisms and suggestions.Keywords
- Complexity
- Condensed matter physics
- Models
- Molecular biology
- Physics-biology interface
- Simulations
- Systems biology