Three metascientific concepts that have been object of philosophical analysis are the concepts oflaw, model and theory. The aim ofthis article is to present the explication of these concepts, and of their relationships, made within the framework of Sneedean or Metatheoretical Structuralism (Balzer et al. 1987), and of their application to a case from the realm of biology: Population Dynamics. The analysis carried out will make it possible to support, contrary to what some philosophers of science in general and of (...) biology in particular hold, the following claims: a) there are "laws" in biological sciences, b) many of the heterogeneous and different "models" of biology can be accommodated under some "theory", and c) this is exactly what confers great unifying power to biological theories. (shrink)

Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models—acknowledging their status as living beings and as epistemological tools—necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper (...) presents an account of how disease-specific animal models are established by drawing on the example of transgenic mice models for Alzheimer’s disease. We will introduce an account of validation that involves a three-fold process including from human being to experimental organism; from experimental organism to animal model; and from animal model to human patient. This process draws upon clinical relevance as much as scientific practices and results in disease-specific, yet incomplete, animal models. The second part of this paper argues that the incompleteness of models can be described in terms of multi-level abstractions. We qualify this notion by pointing to different experimental techniques and targets of modelling, which give rise to a plurality of models for a specific disease. (shrink)

Diagnoses in medicine are often taken to serve as explanations of patients’ symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. (...) While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient’s symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates. (shrink)

The biological sciences have become increasingly reliant on so-called 'model organisms'. I argue that in this domain, the concept of a descriptive model is essential for understanding scientific practice. Using a case study, I show how such a model was formulated in a preexplanatory context for subsequent use as a prototype from which explanations ultimately may be generated both within the immediate domain of the original model and in additional, related domains. To develop this concept of a descriptive model, I (...) focus on use of the nematode worm Caenorhabditis elegans and the wiring diagrams that were developed as models of its neural structure. In addition, implications of the concept of a descriptive model, particularly its relevance for the data-phenomena distinction as well as its relation to long-standing debates on realism, are briefly examined. (shrink)

Through an examination of the actual research strategies and assumptions underlying the Human Genome Project, it is argued that the epistemic basis of the initial model organism programs is not best understood as reasoning via causal analog models. In order to answer a series of questions about what is being modeled and what claims about the models are warranted, a descriptive epistemological method is employed that uses historical techniques to develop detailed accounts which, in turn, help to reveal forms of (...) reasoning that are explicit, or more often implicit, in the practice of a particular field of scientific study. It is suggested that a more valid characterization of the reasoning structure at work here is a form of case-based reasoning. This conceptualization of the role of model organisms can guide our understanding and assessment of these research programs, their knowledge claims and progress, and their limitations, as well as how we educate the public about this type of biomedical research. (shrink)

Taking as starting point Kuhn’s analysis of science textbooks and its application to Sinnott and Dunn’s (1925), it will be discussed the problem of the existence of laws in biology. In particular, it will be showed, in accordance with the proposals of Darden (1991) and Schaffner (1980, 1986, 1993), the relevance of the exemplars, diagrammatically or graphically represented, in the way in which is carried out the teaching and learning process of classical genetics, inasmuch as the information contained in them, (...) indispensable for the right development of that process, exceeds the information contained in the “laws” linguistically articulated and presented in the textbooks. However, it will be maintained that the information is implicit in the law that according to the structuralist concept of fundamental law and the reconstruction of genetics presented by Balzer & Dawe (1990), and later developed by Balzer & Lorenzano (1997) and Lorenzano (1995, 2000, 2002a) could be considered the fundamental law of classical genetics,the law of matching, clearly identified in this paper. (shrink)

Extrapolation from a well-understood base population to a less-understood target population can fail if the base and target populations are not sufficiently similar. Differences between laboratory mice and humans, for example, can hinder extrapolation in medical research. Mice that carry a partial or complete human physiological system, known as humanized mice, are supposed to make extrapolation more reliable by simulating a variety of human diseases. But what justifies our belief that these mice are similar enough to their human counterparts to (...) simulate human disease? I argue that, unless three requirements are met in the process of humanizing mice, very little does. My requirements are not meant to provide necessary and sufficient conditions that guarantee a particular outcome. Instead, they serve as a heuristic for guiding scientific judgments involving extrapolation. In developing each requirement, I engage with philosophical issues concerning the nature of model-based science and the mechanistic approach (and its limits) to making generalizations in the life sciences. (shrink)

Part I Introduction The specific problem adressed in this thesis is: what is the rational use of theory and experiment in the process of scientific discovery, in theory and in the practice of drug research for Parkinson’s disease? The thesis aims to answer the following specific questions: what is: 1) the structure of a theory?; 2) the process of scientific reasoning?; 3) the route between theory and experiment? In the first part I further discuss issues about rationality in science as (...) introduction to part II, and I present an overview of my case-study of neuropharmacology, for which I interviewed researchers from the Groningen Pharmacy Department, as an introduction to part III. Part II Discovery In this part I discuss three theoretical models of scientific discovery according to studies in the fields of Logic, Cognition, and Computation. In those fields the structure of a theory is respectively explicated as: a set of sentences; a set of associated memory chunks; and as a computer program that can generate the observed data. Rationality in discovery is characterized by: finding axioms that imply observation sentences; heuristic search for a hypothesis, as part of problem solving, by applying memory chunks and production rules that represent skill; and finding the shortest program that generates the data, respectively. I further argue that reasoning in discovery includes logical fallacies, which are neccesary to introduce new hypotheses. I also argue that, while human subjects often make errors in hypothesis evaluation tasks from a logical perspective, these evaluations are rational given a probabilistic interpretation. Part III Neuropharmacology In this last part I discusses my case-study and a model of discovery in a practice of drug research for Parkinson’s disease. I discuss the dopamine theory of Parkinson’s disease and model its structure as a qualitative differential equation. Then I discuss the use and reasons for particular experiments to both test a drug and explore the function of the brain. I describe different kinds of problems in drug research leading to a discovery. Based on that description I distinguish three kinds of reasoning tasks in discovery, inference to: the best explanation, the best prediction and the best intervention. I further demonstrate how a part of reasoning in neuropharmacology can be computationally modeled as qualitative reasoning, and aided by a computer supported discovery system. (shrink)

Neuronal ceroid lipofuscinoses are a group of lethal inherited neurodegenerative disorders in humans and many animal species. Critical reflections on a range of ethical issues concerning NCL have been instigated by my research on sheep and cattle affected with NCL, the claim that these sheep and cattle are useful models for the disease in humans, and engagement with families and support groups. My reflections on moral status of animals and validity of animal models are outlined in this paper.

This paper examines the nature of theory structure in biology and considers the implications of those theoretical structures for theory reduction. An account of biological theories as interlevel prototypes embodying causal sequences, and related to each other by strong analogies, is presented, and examples from the neurosciences are provided to illustrate these middle-range theories. I then go on to discuss several modifications of Nagel''s classical model of theory reduction, and indicate at what stages in the development of reductions these models (...) might best apply. Finally I consider several implications of these analyses of theory structure and reduction for disciplinary integration in biology. (shrink)

This paper argues that Adolf Gr nbaum's evaluation of the scientific status of psychoanalysis is marred by its failure to locate Freud's notion of natural science. Contrary to his claims, Griinbaum does not assess Freud's theory on Freud's own terms. The presuppositions that Griinbaum brings to the question of the scientific status of psychoanalysis are problematic and his criticisms and methodological restrictions may not be defensible when psychoanalysis is taken to develop methodologically out of medical science rather than out of (...) physics. I question the adequacy of the epistemological and methodological norms that Griinbaum brings to his analysis and I examine his arguments against the scientific credibility of Freud's theoretical claims. I argue that Griinbaum fails to consider the tension between clinical practice and psychoanalytic theory, ignores the evolution of Freud's thought and distorts and simplifies the complexity of the domain under investigation. Therefore his conclusions regarding the scientific credibility and evaluation of psychoanalysis are questionable. (shrink)

In this rejoinder to the three preceding comments, I provide some additional philosophical warrant for the biomedical sciences' focus on model organisms. I then relate the inquiries on model systems to the concept of 'deep homology', and indicate that the issues that appear to divide my commentators and myself are in part empirical ones. I cite recent work on model organisms, and especially C. elegans that supports my views. Finally, I briefly readdress some of the issues raised by Developmental Systems (...) Theory. (shrink)