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Interdisciplinary problem- solving: emerging modes in integrative systems biology

  • Original Paper in Philosophy of Biology
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Abstract

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific practices address the challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems.

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Notes

  1. As O’Malley and Dupré point out however there is not a well-developed concept of “system” that all groups and sub-groups share (2005). Further many systems biologists are rather ambivalent towards pursuing a general theory of biological systems and acknowledge that a sufficient class of well-validated and robust models does not yet exist. They describe the current shared commitment of systems biologists as a commitment towards an approach that “foregrounds mathematical modeling in order to transcend piecemeal analysis.” (1273)

  2. This research was funded by the US National Science Foundation.

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Acknowledgments

We appreciate the support of the US National Science Foundation in conducting this research (DRL097394084). Miles MacLeod’s participation was also supported by a postdoctoral fellowship at the Academy of Finland Centre of Excellence in the Philosophy of the Social Sciences, University of Helsinki. Members of the Centre contributed much advice in earlier developments of this paper. We thank the directors of Lab C and Lab G for welcoming us into the lab and the lab-members of those labs for granting us numerous interviews. We thank the members of our research group for contributing valuable insights, especially Vrishali Subramanhian, Lisa Osbeck, Sanjay Chandrasekharan, and Wendy Newstetter. We also thank the three anonymous reviewers whose comments substantially improved the paper.

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Authors and Affiliations

  1. Department of Philosophy, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands

    Miles MacLeod

  2. Department of Psychology, Harvard University, 33 Kirkland St., Cambridge, MA, 02138, USA

    Nancy J. Nersessian

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  1. Miles MacLeod
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  2. Nancy J. Nersessian
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Correspondence to Miles MacLeod.

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MacLeod, M., Nersessian, N.J. Interdisciplinary problem- solving: emerging modes in integrative systems biology. Euro Jnl Phil Sci 6, 401–418 (2016). https://doi.org/10.1007/s13194-016-0157-x

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  • DOI: https://doi.org/10.1007/s13194-016-0157-x

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