Waddington redux: models and explanation in stem cell and systems biology

Abstract

Stem cell biology and systems biology are two prominent new approaches to studying cell development. In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues. Systems biology, in contrast, emphasizes mathematical modeling of cellular systems. For scientists and philosophers interested in development, an important question arises: how should the two approaches relate? This essay proposes an answer, using the model of Waddington's landscape to triangulate between stem cell and systems approaches. This simple abstract model represents development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model can play an updated unificatory role. I examine this model's structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments. On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development.

Systems biology and the integration of mechanistic explanation and mathematical explanation

“…Philosophical accounts of mechanistic explanation have usually been silent about how a mathematical model could contribute to an explanation at all; in fact, causal-mechanistic accounts have been developed as an alternative to traditional models of explanation as derivation from quantitatively formulated laws (Brigandt, 2013a;Craver, 2007). Yet systems biology does appear to explain using equations and quantitative models (Baetu, in press;Fagan, 2012).…”

“…And as a developer of a detailed theory of mechanistic explanation, Carl Craver (2006Craver ( , 2007 has repeatedly emphasized the difference between a model merely representing phenomena (and permitting predictions) and a model actually explaining. For Craver, a mechanistic account explains, while he deems several mathematical models from cognitive science and neuroscience to be phenomenological, i.e., the models describe a phenomenon but fall short of explaining it (Craver, 2006(Craver, , 2007(Craver, , 2008Kaplan & Craver, 2011 Baetu, in press;Bechtel, 2012, this issue;Brigandt, in press;Fagan, 2012;Levy, in press;Levy & Bechtel, 2013). I take up this task, by first offering some general philosophical considerations on when a particular equation is indispensable to a given explanation in a mechanistic context.…”

The Philosophy of Biology

“…It may be, for instance, that the formal structures of these abstract models, constructed as they often are from mathematical-cum-topological relations, license an explanatory prowess of a distinctly stronger sort: instead of merely providing causal explanations of particular states of the systems they represent, they may also elucidate certain modal features of those systems which explain the constraints on all of their possible states (Lange 2013;Huneman 2015;Breidenmoser & Wolkenhauer 2015). Moreover, if the formal structures of these non-mechanistic models are capable of correctly capturing central features of the causal architecture of biological systems (as suggested above), the adoption and subsequent refinement of such models may even heuristically aid in the process of mechanism discovery and elucidation (Fagan 2012;Zednik 2015;Baetu 2015). 14 Explanatory pluralism"s popularity doubtlessly derives in part from this characteristically conciliatory approach: it permits non-mechanistic explanation to be both possible and uniquely powerful without its being methodologically privileged.…”

Introduction to Philosophy of Systems Biology

“…Weiss and Bertalanffy are other precursors whose work is of continued relevance for theory development in contemporary systems biology (see Drack,Chapter 7;Mekios,Chapter 18). Similarly, Fagan (2012) highlights how many aspects in Waddinton's theoretical biology anticipate modern systems biology ideas, including the emphasis on global and dynamic epigenetic properties as a prerequisite for understanding development and heredity (see also Fagan,Chapter 8). Other branches of systems biology draw inspiration primarily from the development of Metabolic Control Analysis, Savageau's Biochemical Systems Theory, or Rosen's theoretical framework for metabolic repair-systems (for references see Hofmeyr, Chapter 11; Voit, Chapter 23).…”