Between 1975 and 1985 a series of experiments demonstrated that cancer, whatever its causative agent, is due to the activation, by modification or overexpression, of a family of genes highly conserved during evolution, called the cellular oncogenes. These genes participate in the control of cell division in every living cell. Their products belong to the regulatory network relaying external signals from the membranes towards the nucleus and allowing cells to adapt their division rate to the demand of the organism. These (...) discoveries constitute what may be called the 'oncogene paradigm'. Although the existence of cellular oncogenes, assumed in early models of oncogenesis, was demonstrated as early as 1976, we will show in this article that this discovery was not sufficient for the development of the new paradigm. We will describe its slow and complex formation between 1980 and 1985 followed by its rapid acceptance by the scientific community. (shrink)

The aim of this paper is to assess the relevance of somatic evolution by natural selection to our understanding of cancer development. I do so in two steps. In the first part of the paper, I ask to what extent cancer cells meet the formal requirements for evolution by natural selection, relying on Godfrey-Smith’s (2009) framework of Darwinian populations. I argue that although they meet the minimal requirements for natural selection, cancer cells are not paradigmatic Darwinian populations. In the second (...) part of the paper, I examine the most important examples of adaptation in cancer cells. I argue that they are not significant accumulations of evolutionary changes, and that as a consequence natural selection plays a lesser role in their explanation. Their explanation, I argue, is best sought in the previously existing wiring of the healthy cells. (shrink)

The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in the philosophy of biology, (...) situating the new ‘mechanismic program’ in this context. I argue that the leading advocates of the mechanismic program (i.e., Craver, Darden, Bechtel, etc.) inadvertently conflate the different senses of ‘mechanism’. Specifically, they all inappropriately endow causal mechanisms with the ontic status of machine mechanisms, and this invariably results in problematic accounts of the role played by mechanism-talk in scientific practice. I suggest that for effective analyses of the concept of mechanism, causal mechanisms need to be distinguished from machine mechanisms, and the new mechanismic program in the philosophy of biology needs to be demarcated from the traditional concerns of mechanistic biology. (shrink)

Thomas S. Kuhn's classic book is now available with a new index.

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

In the 1950s and 1960s, an interfield interaction between molecular biologists and biochemists integrated important discoveries about the mechanism of protein synthesis. This extended discovery episode reveals two general reasoning strategies for eliminating gaps in descriptions of the productive continuity of mechanisms: schema instantiation and forward chaining/backtracking. Schema instantiation involves filling roles in an overall framework for the mechanism. Forward chaining and backtracking eliminate gaps using knowledge about types of entities and their activities. Attention to mechanisms highlights salient features of (...) this historical episode while providing general reasoning strategies for mechanism discovery. (shrink)

Discovery proceeds in stages of construction, evaluation, and revision. Each of these stages is constrained by what is known or conjectured about what is being discovered. A new characterization of mechanism aids in specifying what is to be discovered when a mechanism is sought. Guidance in discovering mechanisms may be provided by the reasoning strategies of schema instantiation, modular subassembly, and forward/backward chaining. Examples are found in mechanisms in molecular biology, biochemistry, immunology, and evolutionary biology.

The new research program to understand mechanisms in biology has developed rapidly in the last 10 years. Reconsideration of the characterization of mechanisms in biology in the light of this recent work is now in order. This article discusses the perspectival aspect of the characterization of mechanisms, refinements in claims about working entities and kinds of activities, challenges and responses to claims about regularity, productive continuity, and the organizational aspects of a mechanism, and issues about representations of mechanisms in schemas (...) and sketches. †To contact the author, please write to: Committee for Philosophy and the Sciences, Department of Philosophy, 1125A Skinner Building, University of Maryland, College Park, MD 20742 USA; e‐mail: [email protected]. (shrink)

Discovery proceeds in stages of construction, evaluation, and revision. Each of these stages is constrained by what is known or conjectured about what is being discovered. A new characterization of mechanism aids in specifying what is to be discovered when a mechanism is sought. Guidance in discovering mechanisms may be provided by the reasoning strategies of schema instantiation, modular subassembly, and forward/backward chaining. Examples are found in mechanisms in molecular biology, biochemistry, immunology, and evolutionary biology.

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

This paper explores the epistemology of extrapolation from model organisms to humans in molecular medicine. We take into account two common views on the issue, the homology view and the disanalogy view. In response to both interpretations, we argue that the foundational basis of extrapolations cannot simply be provided by homology and that relevant disanalogies can, thanks to the techniques of molecular biology, be experimentally controlled and exploited to allow useful and reliable extrapolations. The case of "humanised mice" in the (...) context of cancer stem cell research provides evidence of how animal models can be construed to approximate bona fide causal analogue models of human diseases. To supplement this view we show how the epistemology of model organisms needs to take into account the engineering side of molecular medicine. Model organisms are often manipulated to create analogies or remove disanalogies with the target system. We maintain that highlighting this feature is fundamental to explain what warrants extrapolation in the search for the molecular causes of disease. (shrink)

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

One of the motivations for Salmon's (1984) causal theory of explanation was the explanatory irrelevance exhibited by many arguments conforming to Hempel's covering-law models of explanation. However, the nexus of causal processes and interactions characterized by Salmon is not rich enough to supply the necessary conception of explanatory relevance. Salmon's (1994) revised theory, which is briefly criticized on independent grounds, fares no better. There is some possibility that the two-tiered structure of explanation described by Salmon (1984) may be pressed into (...) service, but more work would have to be done. Ironically, Salmon's difficulties are similar to those suffered by his seventeenth-century predecessors. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

This paper explores whether natural selection, a putative evolutionary mechanism, and a main one at that, can be characterized on either of the two dominant conceptions of mechanism, due to Glennan and the team of Machamer, Darden, and Craver, that constitute the “new mechanistic philosophy.” The results of the analysis are that neither of the dominant conceptions of mechanism adequately captures natural selection. Nevertheless, the new mechanistic philosophy possesses the resources for an understanding of natural selection under the rubric.