Causal Graphs and Biological Mechanisms
Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative w
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Causal Graphs and Biological Mechanisms Alexander Gebharter and Marie I. Kaiser
Abstract Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice shows the need for quantitative, probabilistic models of mechanisms, too. In this chapter, we argue that the formal framework of causal graph theory is well suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the basis of an example from contemporary biological practice, namely, feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multilevel character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes while being insufficient for others.
The order of authorship is alphabetical; both authors contributed equally to this chapter. A. Gebharter () Heinrich-Heine-Universität Düsseldorf, Düsseldorf Center for Logic and Philosophy of Science, Universitätsstraße 1, 40225 Düsseldorf, Germany e-mail: [email protected] M.I. Kaiser Philosophisches Seminar, Universität zu Köln, Richard-Strauss-Str. 2, 50931 Köln, Germany e-mail: [email protected] M.I. Kaiser et al. (eds.), Explanation in the Special Sciences: The Case of Biology and History, Synthese Library 367, DOI 10.1007/978-94-007-7563-3__3, © Springer ScienceCBusiness Media Dordrecht 2014
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A. Gebharter and M.I. Kaiser
Keywords Causal graph theory • Modeling • Mechanism • Probabilistic model • Quantitative model
3.1 Introduction The search for mechanisms that underlie the phenomena under study is ubiquitous in many biological fields. Physiologists seek to find the mechanism for muscle contraction, cancer scientists try to discover the mechanisms that cause cell proliferation, and ecologists aim at elucidating the various mechanisms that bring about the maintenance of species diversity – just to mention a few examples. In the last 15 years, the philosophical literature on mechanisms has dramatically increased. Among the major proponents of the “new mechanistic philosophy” (Skipper and Millstein 2005, p. 327) are Carl Craver (2007), William Bechtel (2006, 2008), Stuart Glennan (2002, 2005), Lindley Darden (2006, 2008), and Peter Machamer et al. (2000). Accor
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