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. (shrink)

The experimental interventions that provide evidence of causal relations are notably similar to those that provide evidence of constitutive relevance relations. In the first two sections, I show that this similarity creates a tension: there is an inconsistent triad between Woodward’s popular interventionist theory of causation, Craver’s mutual manipulability account of constitutive relevance in mechanisms, and a variety of arguments for the incoherence of inter-level causation. I argue for an interpretation of the views in which the tension is merely apparent. (...) I propose to explain inter-level relations without inter-level causation by appealing to the notion of fat-handed interventions, and an argument against inter-level causation which dissolves the problem. (shrink)

The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...) pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

The mechanistic framework traditionally comes bundled with a multi-level view. Some ascribe ontological weight to these levels, whereas others claim that characterising a higher-level entity and the corresponding lower-level mechanism are only different descriptions of the same thing. The goal of this paper is to develop a consistent metaphysical picture that can underly the latter position. According to this flat view, wholes and their parts are embedded in the same network of interacting units. The flat view preserves the original virtues (...) of the mechanistic approach and is able to avoid the problems associated with the multi-level view. (shrink)

Piccinini and Craver (Synthese 183:283–311, 2011) argue for the surprising view that psychological explanation, properly understood, is a species of mechanistic explanation. This contrasts with the ‘received view’ (due, primarily, to Cummins and Fodor) which maintains a sharp distinction between psychological explanation and mechanistic explanation. The former is typically construed as functional analysis, the analysis of some psychological capacity into an organized series of subcapacities without specifying any of the structural features that underlie the explanandum capacity. The latter idea, of (...) course, sees explanation as a matter of describing structures that maintain (or produce) the explanandum capacity. In this paper, I defend the received view by criticizing Piccinini and Craver’s argument for the claim that psychological explanation is not distinct from mechanistic explanation, and by showing how psychological explanations can possess explanatory force even when nothing is known about the underlying neurological details. I conclude with a few brief criticisms about the enterprise of mechanistic explanation in general. (shrink)

On observe une nouvelle tendance dans la philosophie des sciences cognitives, manifeste dans les écrits de Betchel et al. qui met en avant l’importance des explications mécanistes au détriment du rôle explicatif des principes. Cet article est un plaidoyer pour rétablir l’équilibre. Il met l’accent sur l’effort d’explication des effets du niveau de base, l’une des plus importantes découvertes empiriques dans l’histoire de la recherche en catégorisation. L’analyse de trois différentes périodes de cette histoire révèle que le recours aux principes (...) y a joué un rôle crucial. Cependant, afin de reconnaître pleinement le rôle explicatif des principes, nous devrions nous préparer à admettre que les explications déductives-nomologiques ne sont pas les seuls types d’explications basées sur des principes. (shrink)

This review surveys three central issues in philosophy of stem cell biology: the nature of stem cells, stem cell experiments, and explanations of stem cell capacities. First, I argue that the fundamental question ‘what is a stem cell?’ has no single substantive answer. Instead, the core idea is explicated via an abstract model, which accounts for many features of stem cell experiments. The second part of this essay examines several of these features: uncertainty, model organisms, and manipulability. The results shed (...) light on the form of our emerging knowledge of stem cells: mechanistic explanations. The third part of the essay sketches some key features of these explanations, which are constructed by a collaborative experimenting community. (shrink)

Mechanisms are organized collections of objects and activities that underlie certain phenomena/behaviours. In this article, I shall argue that the organizations of mechanisms should be thought of as external relations, namely, as relations that do not entirely depend on their relata’s existence, nor on their natures, nor on their intrinsic properties. After having introduced in the first two sections mechanisms and the ontology of relations, I shall analyse the organizations of mechanisms along four different dimensions: spatial, temporal, causal and hierarchical. (...) I shall demonstrate that each dimension requires that organizations be taken as external relations. Finally, in the last section, I shall anticipate and reply to two objections. (shrink)

What is it for an individual thing in the natural world—a rock, a mouse, a family or a planet—to be made of other things—crystals, organs, animals, soil, water, or dirt? Rocks, mice, families and planets are composites, but how are we to understand the relation that holds between these composites and their component parts? My aim is to offer a new account of this relation, which I shall call corporeal composition. A central claim of my account is that corporeal composition (...) is grounded in causal relations between components. I will show how this claim, combined with a minimalist approach to causation—that causation is not one thing, but many—entails a position I call compositional minimalism—that composition is not one thing, but many. (shrink)