Melinda Bonnie Fagan

This paper examines a case of failed interdisciplinary collaboration, between experimental stem cell research and theoretical systems biology. Recently, two groups of theoretical biologists have proposed dynamical systems models as a basis for understanding stem cells and their distinctive capacities. Experimental stem cell biologists, whose work focuses on manipulation of concrete cells, tissues and organisms, have largely ignored these proposals. I argue that ‘failure to communicate’ in this case is rooted in divergent views of explanation: the theoretically-inclined modelers are committed to a version of the covering-law view, while experimental stem cell biologists aim at mechanistic explanations. I propose a way to reconcile these two explanatory approaches to cell development, and discuss the significance of this result for interdisciplinary collaboration in systems biology and beyond

This paper aims to bring the epistemic dimensions of stem cell experiments out of the background, and show that they can be critically evaluated. After introducing some basic concepts of stem cell biology, I set out the current “gold standard” for experimental success in that field (§2). I then trace the origin of this standard to a 1988 controversy over blood stem cells (§3). Understanding the outcome of this controversy requires attention to the details of experimental techniques, the organization of epistemic communities, and relations between the two (§4). With its resolution, a standard for experimental success was established for HSC research, which in turn serves as an exemplar for studies of other stem cells. This historical case study reveals a robust standard for experimental success in stem cell biology: to trace processes of development at the single-cell level, in the form of cell lineage hierarchies. Experiments conforming to this standard can be further critically assessed as means to the therapeutic end of stem cell research: use of stem cells to repair human organs and tissues.

Evolutionary systems biology (ESB) aims to integrate methods from systems biology and evolutionary biology to go beyond the current limitations in both fields. This article clarifies some conceptual difficulties of this integration project, and shows how they can be overcome. The main challenge we consider involves the integration of evolutionary biology with developmental dynamics, illustrated with two examples. First, we examine historical tensions between efforts to define general evolutionary principles and articulation of detailed mechanistic explanations of specific traits. Next, these tensions are further clarified by considering a recent case from another field focused on developmental dynamics: stem cell biology. In the stem cell case, incompatible explanatory aims block integration. Experimental approaches aim at mechanistic explanation while dynamical system models offer explanation in terms of general principles. We then discuss an ESB case in which integration succeeds: search for general attractors using a dynamical systems framework synergizes with the experimental search for detailed mechanisms. Contrasts between the positive and negative cases suggest general lessons for achieving an integrated understanding of developmental and evolutionary dynamics. The key integrative move is to acknowledge two complementary aims, both relevant to explanation: identifying the space of possible dynamic states and trajectories, and mechanistic understanding of causal interactions underlying a specific phenomenon of interest. These two aims can support one another in a joint project characterizing dynamic aspects of evolving lineages. This more inclusive project can lead to insights that cannot be reached by either approach in isolation.

Philosophy of scientific practice aims to critically evaluate as well as describe scientific inquiry. Epistemic norms are required for such evaluation. Social constructivism is widely thought to oppose this critical project. I argue, however, that one variety of social constructivism, focused on epistemic justification, can be a basis for critical epistemology of scientific practice, while normative accounts that reject this variety of social constructivism cannot., idealized epistemic norms cannot ground effective critique of our practices. I propose a new approach, placing SCj within a general framework of social action theory. This framework can be used to explicate epistemic norms implicit in our scientific practices. *Received July 2009; revised July 2009. †To contact the author, please write to: MS 14, P.O. Box 1892, Houston, TX 77251‐1892; e‐mail: [email protected]

It is widely assumed that mechanistic explanations are causal explanations. Many prominent new mechanists endorse interventionism as the correct analysis of explanatory causal models in biology and other fields. This article argues that interventionism is not entirely satisfactory in this regard. A case study of Jacob and Monod’s operon model shows that at least some important mechanistic explanations in biology present significant contrasts with the interventionist account. This result motivates a more inclusive approach to mechanistic explanation, allowing for noncausal aspects.

Philosophical debates about collective scientific knowledge concern two distinct theses: (1) groups are necessary to produce scientific knowledge, and (2) groups have scientific knowledge in their own right. Thesis (1) has strong support. Groups are required, in many cases of scientific inquiry, to satisfy methodological norms, to develop theoretical concepts, or to validate the results of inquiry as scientific knowledge. So scientific knowledge‐production is collective in at least three respects. However, support for (2) is more equivocal. Though some examples suggest that groups have scientific knowledge independently of their individual members, these cases are also explained in terms of relational complexes of members’ beliefs.

Stem cells are defined as having capacities for both self-renewal and differentiation. Many different entities satisfy this working definition. I show that this general stem cell concept is relative to a cell lineage, temporal duration, and characters of interest. Experiments specify values for these variables. So claims about stem cells must be understood in terms of experimental methods used to identify them. Furthermore, the stem cell concept imposes evidential constraints on interpretation of experimental results. From these constraints, it follows that claims about stem cell capacities are inherently uncertain. This result has important implications for stem cell research