Aristotle is oftentimes viewed through a strictly philosophical lens as heir to Plato and has having introduced logical rigor where an emphasis on the theory of Forms formerly prevailed. It must be appreciated that Aristotle was the son of a physician, and that his inculcation of the thought of other Greek philosophers addressing health and the natural elements led to an extremely broad set of biologically- and medically-related writings. As this article proposes, Aristotle deepened the fourfold theory of the elements (...) with anatomic and physiologic observations. In books like History of Animals, Parts of Animals, and the lost Anatomai, he actively dissected organisms and recorded his findings. The corpus of medically-related literature Aristotle developed had a direct influence on subsequent Greek thinkers, including Galen, and on Medieval Islamic and modern Western practitioners such as William Harvey. Aristotle's ideas continue to influence modern medical thinkers in Europe and America through both his interpretation by European philosophers gaining the attention of medical humanists, and his writings' enduring impact on medical researchers balancing scientific with more personalistic approaches to medicine. (shrink)

In this paper I discuss how, given the complexity of biological systems, reliance on theoretical models in the development and testing of biological theories leads to an uncomfortable form of anti-realism. I locate the source of this discomfort in the uniqueness and hence diversity of biological phenomena, in contrast with the simplicity and uniformity of the subject matter of physics. I have argued elsewhere that the use of theoretical models creates an unresolvable tension between the explanatory strength and predictive power (...) of hypotheses, and I review this argument again here. My discussion parallels that of Nancy Cartwright, who claims that the use of ceteris paribus laws in physics creates an antagonism between truth and explanation that requires theoretical models to figure centrally in scientific explanation, thereby precluding realism. I argue instead that in biology it is the use of theoretical models that creates this conflict, and conclude that adequate biological explanation cannot rely on the modeling approach alone. Finally, I claim that if we accept the semantic view of theories, which makes theoretical models an integral part of our conception of theories, we must accept anti-realism as well. (shrink)

Traction forces developed by most cell types play a significant role in the spatial organisation of biological tissues. However, due to the complexity of cell-extracellular matrix interactions, these forces are quantitatively difficult to estimate without explicitly considering cell properties and extracellular mechanical matrix responses. Recent experimental devices elaborated for measuring cell traction on extracellular matrix use cell deposits on a piece of gel placed between one fixed and one moving holder. We formulate here a mathematical model describing the dynamic behaviour (...) of the cell-gel medium in such devices. This model is based on a mechanical force balance quantification of the gel visco-elastic response to the traction forces exerted by the diffusing cells. Thus, we theoretically analyzed and simulated the displacement of the free moving boundary of the system under various conditions for cells and gel concentrations. This modelis then used as the theoretical basis of an experimental device where endothelial cells are seeded on a rectangular biogel of fibrin cast between two floating holders, one fixed and the other linked to a force sensor. From a comparison of displacement of the gel moving boundary simulated by the model and the experimental data recorded from the moving holder displacement, the magnitude of the traction forces exerted by the endothelial cell on the fibrin gel was estimated for different experimental situations. Different analytical expressions for the cell traction term are proposed and the corresponding force quantifications are compared to the traction force measurements reported for various kind of cells with the use of similar or different experimental devices. (shrink)

Many scientific models in biology are how-possibly models. These models depict things as they could be, but do not necessarily capture actual states of affairs in the biological world. In contemporary philosophy of science, it is customary to treat how-possibly models as second-rate theoretical tools. Although possibly important in the early stages of theorizing, they do not constitute the main aim of modelling, namely, to discover the actual mechanism responsible for the phenomenon under study. In the paper it is argued (...) that this prevailing picture does not do justice to the synthetic strategy that is commonly used in biological engineering. In synthetic biology, how-possibly models are not simply speculations or eliminable scaffolds towards a single how-actually model, but indispensable design hypotheses for a field whose ultimate goal is to build novel biological systems. The paper explicates this by providing an example from the study of alternative genetic systems by synthetic biologist Steven Benner and his group. The case will also highlight how the method of synthesis, even when it fails, provides an effective way to limit the space of possible models for biological systems. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology -- unlike historians and social scientists -- had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology as a (...) unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology -- described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details" -- and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism -- defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics. The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development. (shrink)

We used agent-based modelling to highlight the advantages and disadvantages of several management styles in biology, ranging from centralized to egalitarian ones. In egalitarian groups, all team members are connected with each other, while in centralized ones, they are only connected with the principal investigator. Our model incorporated time constraints, which negatively influenced weakly connected groups such as centralized ones. Moreover, our results show that egalitarian groups outperform others if the questions addressed are relatively simple or when the communication among (...) agents is limited. Complex epistemic spaces are explored best by centralized groups. They outperform other team structures because the individual members can develop their own ideas with less interference of the opinions of others. The optimal ratio between time spent on experimentation and dissemination varies between different organizational structures. Furthermore, if the evidence is shared only after a relevant degree of certainty is reached, all investigated groups epistemically profit. We discovered that the introduction of seminars to the model changes the epistemic performance in favour of weakly connected teams. Finally, the abilities of the principal investigator do not seem to outperform cognitive diversity, as group performances were not strongly influenced by the increase of her abilities. (shrink)

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)

This paper is aimed at identifying how a model’s explanatory power is constructed and identified, particularly in the practice of template-based modeling (Humphreys, Philos Sci 69:1–11, 2002; Extending ourselves: computational science, empiricism, and scientific method, 2004), and what kinds of explanations models constructed in this way can provide. In particular, this paper offers an account of non-causal structural explanation that forms an alternative to causal–mechanical accounts of model explanation that are currently popular in philosophy of biology and cognitive science. Clearly, (...) defences of non-causal explanation are far from new (e.g. Batterman, Br J Philos Sci 53:21–38, 2002a; The devil in the details: asymptotic reasoning in explanation, reduction, and emergence, 2002b; Pincock, Noûs 41:253–275, 2007; Mathematics and scientific representation 2012; Rice, Noûs. doi:10.1111/nous.12042, 2013; Biol Philos 27:685–703, 2012), so the targets here are focused on a particular type of robust phenomenon and how strong invariance to interventions can block a range of causal explanations. By focusing on a common form of model construction, the paper also ties functional or computational style explanations found in cognitive science and biology more firmly with explanatory practices across model-based science in general. (shrink)

Two decades of critique have sensitized historians and philosophers of science to the inadequacies of conventional dichotomies between theory and practice, thereby prompting the search for new ways of writing about science that are less beholden than the old ways to the epistemological mores of theoretical physics, and more faithful to the actual practices not only of physics but of all the natural sciences. The need for alternative descriptions seems particularly urgent if one is to understand the place of theory (...) (and, in parallel, the role of modeling) in contemporary molecular biology, a science where, until now, no division between theory and experiment has obtained, and where distinctions between representing and intervening, and more generally, between basic and applied science, are daily becoming more blurred. Indeed, the very division between theory and experiment threatens to slight the extensive and sophisticated theoretical analyses (and even modeling) on which experimental work in contemporary molecular biology so often depends. My aim in this paper is to find a way of talking about theoretical practices in biology that is directly rooted in the mix of conceptual and material work that biologists do. As an example of such theoretical practices, I choose for the focus of my analysis the development of a model for gene regulation out of the experimental work of Eric Davidson and his colleagues at Cal Tech. (shrink)

In Making Sense of Life , Keller emphasizes several differences between biology and physics. Her analysis focuses on significant ways in which modelling practices in some areas of biology, especially developmental biology, differ from those of the physical sciences. She suggests that natural models and modelling by homology play a central role in the former but not the latter. In this paper, I focus instead on those practices that are importantly similar, from the point of view of epistemology and cognitive (...) science. I argue that concrete and abstract models are significant in both disciplines, that there are shared selection criteria for models in physics and biology, e.g. familiarity, and that modelling often occurs in a similar fashion. (shrink)

Mathematical models of biological patterns are central to contemporary biology. This paper aims to consider what these models contribute to biology through the detailed consideration of an important case: Hamilton’s selfish herd. While highly abstract and idealized, Hamilton’s models have generated an extensive amount of research and have arguably led to an accurate understanding of an important factor in the evolution of gregarious behaviors like herding and flocking. I propose an account of what these models are able to achieve and (...) how they can support a successful scientific research program. I argue that the way these models are interpreted is central to the success of such programs. (shrink)

The dissemination of models across disciplinary lines has become a phenomenon of interest to philosophers of science. To account for this phenomenon, philosophers have invented two units of analysis. The first identifies to the thing that transfers, model templates. The second identifies the thing to which transferable templates apply, landing zones. There exists a dynamic between the thing that is transferred and the thing to which transferrable templates apply. The use of a transferable template in a new domain requires reconception (...) of domain-specific phenomena. This paper examines two cases of model transfer, the use of the ideal gas law in biology by R.A. Fisher and the use of the virial theorem in chemistry by Richard Bader. These two stories of model transfer in biology and chemistry indicate a dimension to conceptual progress related to this dynamic. Using discourse on model transfer affords philosophers a novel approach for depicting the invention of, for instance, chemical concepts and resulting disputes. (shrink)

This article considers claims that biology should seek general theories similar to those found in physics but argues for an alternative framework for biological theories as collections of prototypical interlevel models that can be extrapolated by analogy to different organisms. This position is exemplified in the development of the Hodgkin‐Huxley giant squid model for action potentials, which uses equations in specialized ways. This model is viewed as an “emergent unifier.” Such unifiers, which require various simplifications, involve the types of heuristics (...) discussed in Wimsatt’s writings on reduction, but with a twist. Here, the heuristics are used to generate emergent rather than reductive explanations. †To contact the author, please write to: Department of History and Philosophy of Science, University of Pittsburgh, 1017 Cathedral of Learning, Pittsburgh, PA 15260; e‐mail: [email protected]. (shrink)

SynopsisThe response to physics and chemistry which characterized mid-nineteenth century physiology took two major directions. One, found most prominently among the German physiologists, developed explanatory models which had as their fundamental assumption the ultimate reducibility of all biological phenomena to the laws of physics and chemistry. The other, characteristic of the French school of physiology, recognized that physics and chemistry provided potent analytical tools for the exploration of physiological activities, but assumed in the construction of explanatory models that the organism (...) involved special levels of organization and that there must, in consequence, be special biological laws.The roots of this argument about concept formation in physiology are explored in the works of Theodor Schwann, Johannes Müller, François Magendie and Claude Bernard among others. (shrink)

The aim of this article is to investigate the relevance and implications of synthetic models for the study of the interactive dimension of minimal life and cognition, by taking into consideration how the use of artificial systems may contribute to an understanding of the way in which interactions may affect or even contribute to shape biological identities. To do so, this article analyzes experimental work in synthetic biology on different types of interactions between artificial and natural systems, more specifically: between (...) protocells and between biological living cells and protocells. It discusses how concepts such as control, cognition, communication can be used to characterize these interactions from a theoretical point of view, which criteria of relevance and evaluation of synthetic models can be applied to these cases, and what are their limits. (shrink)

Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...) testing, comparing, and revising models, and much journal space is dedicated to interpreting and discussing the implications of models. In short, models are one of the principal instruments of modern science. (shrink)

Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia—the existence of a direct and an indirect pathway that compete against each other. This characteristic has important consequences in decision-making tasks, which are brought to light by Parkinson's disease as (...) well as genetic differences in dopamine receptors. This paper shows that a standard model of action selection in a cognitive architecture cannot replicate any of these findings, details an alternative solution that reconciles action selection in the architecture with the physiology of the basal ganglia, and extends the domain of application of cognitive architectures. The implication of this solution for other architectures and existing models are discussed. (shrink)

The practical criteria by which developmental biologists choose their model systems have evolutionary correlates. The result is a sample that is not merely small, but biased in particular ways, for example towards species with rapid, highly canalized development. These biases influence both data collection and interpretation, and our views of how development works and which aspects of it are important.

Propositions alone are not constitutive of science. But is the "non-propositional" side of science theoretically superfluous: must philosophy of science consider it in order to adequately account for science? I explore the boundary between the propositional and non-propositional sides of biological theory, drawing on three cases: Grinnell's remnant models of faunas, Wright's path analysis, and Weismannism's role in the generalization of evolutionary theory. I propose a picture of material model-building in biology in which manipulated systems of material objects function as (...) theoretical models. In each of the cases, material systems such as diagrams play important generative as well as presentational roles. (shrink)

In recent years, there has much attention given by philosophers to the ubiquitous role of models and modeling in the biological sciences. Philosophical debates has focused on several areas of discussion. First, what are models in the biological sciences? The term ‘model’ is applied to mathematical structures, graphical displays, computer simulations, and even concrete organisms. Is there an account which unifies these disparate structures? Second, scientists routinely distinguish between theories and models; however, this distinction is more difficult to draw in (...) the biological sciences since biologists often only have a variety of models and rarely have something like a fundamental theory. What then is a theory in biology? Third, how are models related to empirical or “target” systems? (shrink)

In Making Sense of Life, Keller emphasizes several differences between biology and physics. Her analysis focuses on significant ways in which modelling practices in some areas of biology, especially developmental biology, differ from those of the physical sciences. She suggests that natural models and modelling by homology play a central role in the former but not the latter. In this paper, I focus instead on those practices that are importantly similar, from the point of view of epistemology and cognitive science. (...) I argue that concrete and abstract models are significant in both disciplines, that there are shared selection criteria for models in physics and biology, e.g. familiarity, and that modelling often occurs in a similar fashion. (shrink)

Stem cell scientists and ethicists have focused intently on questions relevant to the developmental stage and developmental capacities of stem cells. Comparably less attention has been paid to an equally important set of questions about the nature of stem cells, their common characteristics, their non‐negligible differences and their possible developmental species specificity. Answers to these questions are essential to the project of justly inferring anything about human stem cell biology from studies in non‐human model systems—and so to the possibility of (...) eventually developing human therapies based on stem cell biology. After introducing and discussing these questions, I conclude with a brief discussion of the creation of novel model systems in stem cell biology: human‐to‐animal embryonic chimeras. Such novel model systems may help to overcome obstacles to extrapolation, but they are also scientifically and ethically contentious. BioEssays 26:1005‐1012, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

The dissemination of models across disciplinary lines has become a phenomenon of interest to philosophers of science. To account for this phenomenon, philosophers have invented two units of analysis. The first identifies to the thing that transfers, model templates. The second identifies the thing to which transferable templates apply, landing zones. There exists a dynamic between the thing that is transferred and the thing to which transferrable templates apply. The use of a transferable template in a new domain requires reconception (...) of domain-specific phenomena. This paper examines two cases of model transfer, the use of the ideal gas law in biology by R.A. Fisher and the use of the virial theorem in chemistry by Richard Bader. These two stories of model transfer in biology and chemistry indicate a dimension to conceptual progress related to this dynamic. Using discourse on model transfer affords philosophers a novel approach for depicting the invention of, for instance, chemical concepts and resulting disputes. (shrink)

The dissemination of models across disciplinary lines has become a phenomenon of interest to philosophers of science. To account for this phenomenon, philosophers have invented two units of analysis. The first identifies to the thing that transfers, model templates. The second identifies the thing to which transferable templates apply, landing zones. There exists a dynamic between the thing that is transferred and the thing to which transferrable templates apply. The use of a transferable template in a new domain requires reconception (...) of domain-specific phenomena. This paper examines two cases of model transfer, the use of the ideal gas law in biology by R.A. Fisher and the use of the virial theorem in chemistry by Richard Bader. These two stories of model transfer in biology and chemistry indicate a dimension to conceptual progress related to this dynamic. Using discourse on model transfer affords philosophers a novel approach for depicting the invention of, for instance, chemical concepts and resulting disputes. (shrink)

This study aimed at determining B.S. Biology students’ comprehension of the Bioethics principles and conviction schemas towards bioethical issues; as well as at identifying predictors for comprehension of bioethical principles and convictions and creating model constructs of predictors which are fit for the data. One-hundred sixteen Filipino Biology majors were pre and post-tested for comprehension of bioethics principles and convictions towards bioethical issues. Predictors for comprehension and convictions among personal and family background factors, global and primary personality factors, and mental (...) ability were identified through step-wise multiple regression. Constructed path models were tested for goodness of fit using Structural Equation Modeling. Results showed that case study discussion and the bioethics course had positive effects on comprehension of the bioethics principles and on convictions towards bioethical issues. Predictors for comprehension of Bioethics principles before intervention were verbal ability, warmth, and exposure to media. Sex and openness to change were predictors for pre-convictions. Post-conviction predictors were anxiety, self-control, extraversion, liveliness, and perfectionism. Four out of five model constructs were accepted based on model fit criteria. In conclusion, personal factors, i.e., sex and personality factors are contributors in bioethical convictions; not cognitive factors like mental ability or comprehension of Bioethics principles; implying that bioethical convictions are already pre-conceived and that empathy-based experiences may strengthen convictions towards bioethical issues. (shrink)

In addition to its obvious successes within the kinetic theory the ideal gas law and the modeling assumptions associated with it have been used to treat phenomena in domains as diverse as economics and biology. One reason for this is that it is useful to model these systems using aggregates and statistical relationships. The issue I deal with here is the way R. A. Fisher used the model of an ideal gas as a methodological device for examining the causal role (...) of selection in producing variation in Mendelian populations. The model enabled him to create the kind of population where one could measure the effects of selection in a way that could not be done empirically. Consequently we are able to see how the model of an ideal gas was transformed into a biological model that functioned as an instrument for both investigating nature and developing a new theory of genetics. (shrink)

This paper analyses conceptual and experimental work in synthetic biology on different types of interactions considered as minimal examples or models of communication. It discusses their pertinence and relevance for the wider understanding of this biological and cognitive phenomenon. It critically analyses their limits and it argues that a conceptual framework is needed. As a possible solution, it provides a theoretical account of communication based on the notion of organisation, and characterised in terms of the functional influence exerted by the (...) sender upon the receiver. It shows that this account can be operationalised in synthetic biology, and that it can supply criteria and guidelines for the design and evaluation of synthetic models. (shrink)

Ruth Millikan is well known for having developed a strikingly original way for philosophers to seek understanding of mind and language, which she sees as biological phenomena. She now draws together a series of groundbreaking essays which set out her approach to language. Guiding the work of most linguists and philosophers of language today is the assumption that language is governed by prescriptive normative rules. Millikan offers a fundamentally different way of viewing the partial regularities that language displays, comparing them (...) to biological norms that emerge from natural selection. This yields novel and quite radical consequences for our understanding of the nature of public linguistic meaning, the process of language understanding, how children learn language, and the semantics/pragmatics distinction. (shrink)

Simulation and Similarity: Using Models to Understand the World is an account of modeling in contemporary science. Modeling is a form of surrogate reasoning where target systems in the natural world are studied using models, which are similar to these targets. My book develops an account of the nature of models, the practice of modeling, and the similarity relation that holds between models and their targets. I also analyze the conceptual tools that allow theorists to identify the trustworthy aspects of (...) models. Taken as a whole, I try to account for the ways that modeling is actually practiced by theorists, while abstracting sufficiently to understand the similarities and differences among examples of concrete, mathematical, and computational modeling.I am grateful to Wendy Parker, Jay Odenbaugh, and Bill Wimsatt for their careful and interesting reading of my book, as well as their constructive criticisms. Although I naturally disagree with some of their critiques, I have learned much .. (shrink)

Predictions about the health risks of low level radiation combine two sorts of measures. One estimates the amount and kinds of radiation released into the environment, and the other estimates the adverse health effects. A new field called health physics integrates and applies nuclear physics to cytology to supply both these estimates. It does so by first determining the kinds of effects different types of radiation produce in biological organisms, and second, by monitoring the extent of these effects produced by (...) given levels of exposure. This essay examines the interplay between evidential constraints and external, contextual interests and values in studying the biological hazards of radiation. By analyzing the debate over linear vs. quadratic dose response models, the essay focuses on problems of developing quantitative, rather than qualitative, estimates of the risks of increased cancer incidence in an exposed population. (shrink)

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models – the representation of a hypothesis about a target system – are distinguished from several other relationships also termed “modelling” in discussions of scientific explanation. Seven dimensions on which (...) simulation models can differ are defined and distinctions between them discussed: 1. Relevance: whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments. Key Words: animal behaviour; levels; models; neuroethology; realism; robotics; simulation. (shrink)

: Models that fail to satisfy the Markov condition are unstable in the sense that changes in state variable values may cause changes in the values of background variables, and these changes in background lead to predictive error. This sort of error arises exactly from the failure of non-Markovian models to track the set of causal relations upon which the values of response variables depend. The result has implications for discussions of the level of selection: under certain plausible conditions the (...) models of selection presented in such debates will not satisfy the Markov condition when fit to data from real populations. Since this is true both for group and individual level models, models of neither sort correctly represent the causal structure generating, nor correctly explain, the phenomena of interest. (shrink)

Catastrophe Theory was developed in an attempt to provide a form of Mathematics particularly apt for applications in the biological sciences. It was claimed that while it could be applied in the more conventional physical way, it could also be applied in a new metaphysical way, derived from the Structuralism of Saussure in Linguistics and Lévi-Strauss in Anthropology.Since those early beginnings there have been many attempts to apply Catastrophe Theory to Biology, but these hopes cannot be said to have been (...) fully realised. (shrink)

The temporal behaviour of the nonlinear compartmental model we have developed for rat calcium metabolism is discussed with respect to the theoretical properties of the self-oscillating autocatalytic subunit around which the model is constructed. Depending on the approximations made, this subunit is described by a minimal two-variable model, SU2, or by a three-variable one, SU3. The diversity of the theoretical dynamic behaviours possible with SU2 is greatly increased with SU3. But the identification of SU3 parameter values in three different experimental (...) situations reveals that biological constraints efficiently preserve a simple circadian rhythm for bone metabolism. This analysis indicates the significant contribution of the available bone crystal pool to the dynamic organization of this tissue, and hence to extracellular calcium homeostasis. (shrink)

Eye movement desensitization and reprocessing therapy is a well-established therapeutic method to treat post-traumatic stress disorder. However, how EMDR exerts its therapeutic action has been studied in many types of research but still needs to be completely understood. This is in part due to limited knowledge of the neurobiological mechanisms underlying EMDR, and in part to our incomplete understanding of PTSD. In order to model PTSD, we used a biologically inspired computational model based on firing rate units, encompassing the cortex, (...) hippocampus, and amygdala. Through the modulation of its parameters, we fitted real data from patients treated with EMDR or classical exposure therapy. This allowed us to gain insights into PTSD mechanisms and to investigate how EMDR achieves trauma remission. (shrink)

Instead of arguing for a specific animal model, Striedter will review the history and philosophy of animal models in biomedical research, examining their various advantages and limitations.

The aim of the study is to contribute to a better understanding of some aspects of the structure of biological knowledge and to make clearer to what extent the methods of reasoning may be useful in this field when only qualitative information is available. A fragment of biological knowledge (theory of cell motility) is analysed from the logico-methodological point of view as a coherent system and the possibility of its formal representation is investigated. The analysis is based on distinguishing the (...) main objects and their features (attributes) of which a given piece of knowledge is composed and on the values which these features may display. The features are interconnected by relations (in which various number of arguments appear) and these relations constitute the main (general, higher level) laws of a given fragment of knowledge (theory). Values of attributes are also mutually connected and these relations correspond to the detailed (lower level) laws. A computer system (in which Prolog language was used) enables to perform inference operations of progressive as well as regressive type. The main categories of reasoning procedures are described and illustrated by examples, namely a) search for conclusions which may be confronted with the actual knowledge in order to verify the system as a whole, b) formation of working hypotheses in the process of their empirical verification and explanation of facts and laws. The problem of development and modification of the system is also discussed. (shrink)

The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research. My purpose is not only to suggest a new taxonomy of robustness, but also to argue that previous authors have concentrated on a narrow sense of robustness analysis, which they have inadequately distinguished (...) from other investigations of models such as sensitivity analysis. (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)

John Maynard Smith is the person most responsible for the use of game theory in evolutionary biology, having introduced and developed its major concepts, and later surveyed its uses. In this paper I look at some rhetorical work done by Maynard Smith and his co-author G.R. Price to make game theory a standard and common modelling tool for the evolutionary study of behavior. The original presentation of the ideas — in a 1973 Nature article — is frequently cited but almost (...) certainly rarely read. It took reformulation of the approach to create a usable model and an object of study. Perhaps paradoxically, the new model dealt with more abstract objects than did its predecessor, but because of that a better case could be made for its realism. The particular strategy of abstraction allowed game-theoretic modelling to gain a certain measure of autonomy from empirical problems, and thus to flourish. (shrink)

Biosemiotics is a growing fi eld that investigates semiotic processes in the living realm in an attempt to combine the fi ndings of the biological sciences and semiotics. Semiotic processes are more or less what biologists have typically referred to as “ signals, ” “ codes, ”and “ information processing ”in biosystems, but these processes are here understood under the more general notion of semiosis, that is, the production, action, and interpretation of signs. Thus, biosemiotics can be seen as biology (...) interpreted as a study of living sign systems — which also means that semiosis or sign process can be seen as the very nature of life itself. In other words, biosemiotics is a field of research investigating semiotic processes (meaning, signification, communication, and habit formation in living systems) and the physicochemical preconditions for sign action and interpretation. -/- (...). (shrink)

The prevalence of optimality models in the literature of evolutionary biology is testimony to their popularity and importance. Evolutionary biologist R. C. Lewontin, whose criticisms of optimality models are considered here, reflects that "optimality arguments have become extremely popular in the last fifteen years, and at present represent the dominant mode of thought." Although optimality models have received little attention in the philosophical literature, these models are very interesting from a philosophical point of view. As will be argued, optimality models (...) are central to evolutionary thought, yet they are not readily accomodated by the traditional view of scientific theories. According to the traditional view, we would expect optimality models to employ general, empirical laws of nature, but they do not. Fortunately, the semantic view of scientific theories, a recent alternative to the traditional view, more readily accomodates optimality models. As we would expect on the semantic view, optimality models can be construed as specifications of ideal systems. These specifications may be used to describe empirical systems--that is, the specifications may have empirical instances. But the specifications are not empirical claims, much less general, empirical laws. Although philosophers have yet to discuss the general features and uses of optimality models, these topics have stimulated much recent discussion among evolutionary biologists. Their discussions raise a number of precautions concerning the proper use of optimality models. Moreover, many of their caveats can be interpreted as general reminders that 1) optimality models specify ideal systems whose empirical instantiations may be quite restricted, and that 2) optimality models should not be construed as general, empirical laws. As G. F. Oster and E. O. Wilson caution, "the prudent course is to regard optimality models as provisional guides to further empirical research and not necessarily as the key to deeper laws of nature." It seems, then, that the semantic view of theories is more sensitive to the nature and limitations of optimality models than is the more traditional view of theories. (shrink)

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. (shrink)